&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2 class=&quot;heading&quot;&gt;About the role:&lt;/h2&gt;
&lt;p&gt;When you see what modern language models are capable of, do you wonder, &quot;How do these things work? How can we trust them?&quot;&lt;/p&gt;
&lt;p&gt;The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;People mean many different things by &quot;interpretability&quot;. We&#39;re focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do &quot;biology&quot; or &quot;neuroscience&quot; of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we&#39;re trying to &quot;reverse engineer&quot;.&lt;/p&gt;
&lt;p&gt;A few places to learn more about our work and team at a high level are &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://www.youtube.com/watch?v=TxhhMTOTMDg&quot; target=&quot;_blank&quot;&gt;this introduction to Interpretability&lt;/a&gt; from our research lead, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://colah.github.io/about.html&quot; target=&quot;_blank&quot;&gt;Chris Olah&lt;/a&gt;; a &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://open.spotify.com/episode/5UF79Uu94ia0fwC32a89LU&quot; target=&quot;_blank&quot;&gt;discussion of our work&lt;/a&gt; on the &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://www.nytimes.com/column/hard-fork&quot; target=&quot;_blank&quot;&gt;Hard Fork podcast&lt;/a&gt; produced by the New York Times, and this &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://www.anthropic.com/research/engineering-challenges-interpretability&quot; target=&quot;_blank&quot;&gt;blog post&lt;/a&gt; (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team&#39;s notable publications include &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2021/framework/index.html&quot; target=&quot;_blank&quot;&gt;A Mathematical Framework for Transformer Circuits&lt;/a&gt;, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2022/in-context-learning-and-induction-heads/index.html&quot; target=&quot;_blank&quot;&gt;In-context Learning and Induction Heads&lt;/a&gt;, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot; target=&quot;_blank&quot;&gt;Toy Models of Superposition&lt;/a&gt;, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2024/scaling-monosemanticity/&quot; target=&quot;_blank&quot;&gt;Scaling Monosemanticity&lt;/a&gt;, and our Circuits’ &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/methods.html&quot; target=&quot;_blank&quot;&gt;Methods&lt;/a&gt; and &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/biology.html&quot; target=&quot;_blank&quot;&gt;Biology&lt;/a&gt; papers. This work builds on ideas from members&#39; work prior to Anthropic such as the &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://distill.pub/2020/circuits/&quot; target=&quot;_blank&quot;&gt;original circuits thread&lt;/a&gt;, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://distill.pub/2021/multimodal-neurons/&quot; target=&quot;_blank&quot;&gt;Multimodal Neurons&lt;/a&gt;, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://distill.pub/2019/activation-atlas/&quot; target=&quot;_blank&quot;&gt;Activation Atlases&lt;/a&gt;, and &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://distill.pub/2018/building-blocks/&quot; target=&quot;_blank&quot;&gt;Building Blocks&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2023/interpretability-dreams/index.html&quot; target=&quot;_blank&quot;&gt;vision post&lt;/a&gt;). In the short term, we have focused on resolving the issue of &quot;superposition&quot; (see &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot; target=&quot;_blank&quot;&gt;Toy Models of Superposition&lt;/a&gt;, &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2023/toy-double-descent/index.html&quot; target=&quot;_blank&quot;&gt;Superposition, Memorization, and Double Descent&lt;/a&gt;, and our &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2023/may-update/index.html&quot; target=&quot;_blank&quot;&gt;May 2023 update&lt;/a&gt;), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://www.anthropic.com/news/mapping-mind-language-model&quot; target=&quot;_blank&quot;&gt;work&lt;/a&gt; found millions of features in Sonnet, one of our production language models, represents progress in this direction. In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model&#39;s computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks.&lt;/p&gt;
&lt;p&gt;We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer. We also have an &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2024/april-update/index.html#interpretability-architecture&quot; target=&quot;_blank&quot;&gt;Interpretability Architectures project&lt;/a&gt; that involves collaborating with Pretraining.&lt;/p&gt;
&lt;h2 class=&quot;heading&quot;&gt;Responsibilities:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;Develop methods for understanding LLMs by reverse engineering algorithms learned in their weights&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Design and run robust experiments, both quickly in toy scenarios and at scale in large models&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Create and analyze new interpretability features and circuits to better understand how models work.&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Build infrastructure for running experiments and visualizing results&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Work with colleagues to communicate results internally and publicly&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 class=&quot;heading&quot;&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;Have a strong track record of scientific research (in any field), and have done &lt;em&gt;some&lt;/em&gt; work on Interpretability&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Enjoy team science – working collaboratively to make big discoveries&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Are comfortable with messy experimental science. We&#39;re inventing the field as we work, and the first textbook is years away&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;You view research and engineering as two sides of the same coin. Every team member writes code, designs and runs experiments, and interprets results&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;You can clearly articulate and discuss the motivations behind your work, and teach us about what you&#39;ve learned. You like writing up and communicating your results, even when they&#39;re null&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;To learn more about the skills we look for and how to prepare for this role, see our blog post – &lt;a class=&quot;text-accent-secondary-100 underline&quot; href=&quot;https://transformer-circuits.pub/2025/april-update/index.html#work&quot; target=&quot;_blank&quot;&gt;So You Want to Work in Mechanistic Interpretability?&lt;/a&gt;&lt;/p&gt;
&lt;p&gt;Familiarity with Python is required for this role.&lt;/p&gt;
&lt;h2 class=&quot;heading&quot;&gt;&lt;strong&gt;Role Specific Location Policy:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$315,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$560,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Research Scientist, Interpretability

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the Interpretability team:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;When you see what modern language models are capable of, do you wonder, &quot;How do these things work? How can we trust them?&quot;&lt;/p&gt;
&lt;p&gt;The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;People mean many different things by &quot;interpretability&quot;. We&#39;re focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do &quot;biology&quot; or &quot;neuroscience&quot; of neural networks, or as treating neural networks as binary computer programs we&#39;re trying to &quot;reverse engineer&quot;.&lt;/p&gt;
&lt;p&gt;We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our &lt;a href=&quot;https://transformer-circuits.pub/2023/interpretability-dreams/index.html&quot;&gt;vision post&lt;/a&gt;). We have focused on resolving the issue of &quot;superposition&quot; (see &lt;a href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot;&gt;Toy Models of Superposition&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2023/toy-double-descent/index.html&quot;&gt;Superposition, Memorization, and Double Descent&lt;/a&gt;, and our &lt;a href=&quot;https://transformer-circuits.pub/2023/may-update/index.html&quot;&gt;May 2023 update&lt;/a&gt;), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent &lt;a href=&quot;https://www.anthropic.com/news/mapping-mind-language-model&quot;&gt;work&lt;/a&gt; which found millions of features in Claude 3.0 Sonnet, one of our production language models, represents progress in this direction. In our &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/methods.html&quot;&gt;most recent work&lt;/a&gt;, we developed methods that allow us to build circuits using features and use these circuits to understand the mechanisms associated with a model&#39;s computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Claude Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks.&lt;/p&gt;
&lt;p&gt;A few places to learn more about our work and team are this &lt;a href=&quot;https://www.youtube.com/watch?v=TxhhMTOTMDg&quot;&gt;introduction to Interpretability&lt;/a&gt; from our research lead, &lt;a href=&quot;https://colah.github.io/about.html&quot;&gt;Chris Olah, Stanford CS25 lecture given by Josh Batson, and&lt;/a&gt; &lt;a href=&quot;https://twimlai.com/podcast/twimlai/exploring-the-biology-of-llms-with-circuit-tracing/&quot;&gt;TWIML AI podcast&lt;/a&gt; with Emmanuel Ameisen.&lt;/p&gt;
&lt;p&gt;Some of our team&#39;s notable publications include and our Circuits’&amp;nbsp;&lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/methods.html&quot;&gt;Methods&lt;/a&gt; and &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/biology.html&quot;&gt;Biology&lt;/a&gt; papers, &lt;a href=&quot;https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html&quot;&gt;Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2023/monosemantic-features/index.html&quot;&gt;Towards Monosemanticity: Decomposing Language Models With Dictionary Learning&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2021/framework/index.html&quot;&gt;A Mathematical Framework for Transformer Circuits&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2022/in-context-learning-and-induction-heads/index.html&quot;&gt;In-context Learning and Induction Heads&lt;/a&gt;, and &lt;a href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot;&gt;Toy Models of Superposition&lt;/a&gt;. This work builds on ideas from members&#39; work prior to Anthropic such as the &lt;a href=&quot;https://distill.pub/2020/circuits/&quot;&gt;original circuits thread&lt;/a&gt;, &lt;a href=&quot;https://distill.pub/2021/multimodal-neurons/&quot;&gt;Multimodal Neurons&lt;/a&gt;, &lt;a href=&quot;https://distill.pub/2019/activation-atlas/&quot;&gt;Activation Atlases&lt;/a&gt;, and &lt;a href=&quot;https://distill.pub/2018/building-blocks/&quot;&gt;Building Blocks&lt;/a&gt;.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;About the role:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;As a manager on the Interpretability team, you&#39;ll support a team of expert researchers and engineers who are trying to understand at a deep, mechanistic level, how modern large language models work internally.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;Few things can accelerate this work more than great managers. Your work as manager will be critical in making sure that our fast-growing team is able to meet its ambitious safety research goals over the coming years. In this role, you will partner closely with an individual contributor research lead to drive the team&#39;s success, translating cutting-edge research ideas into tangible goals and overseeing their execution. You will manage team execution, careers and performance, facilitate relationships within and across teams, and drive the hiring pipeline.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;If you&#39;re more interested in making individual direct technical contributions to our research as the primary focus of your role, feel free to apply to our &lt;a href=&quot;https://boards.greenhouse.io/anthropic/jobs/4020159008&quot;&gt;Research Scientist&lt;/a&gt; or &lt;a href=&quot;https://boards.greenhouse.io/anthropic/jobs/4020305008&quot;&gt;Research Engineer&lt;/a&gt; roles instead.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Partner with a research lead on direction, project planning and execution, hiring, and people development&lt;/li&gt;
&lt;li&gt;Set and maintain a high bar for execution speed and quality, including identifying improvements to processes that help the team operate effectively&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Coach and support team members to have more impact and develop in their careers&lt;/li&gt;
&lt;li&gt;Drive the team&#39;s recruiting efforts, including hiring planning, process improvements, and sourcing and closing&lt;/li&gt;
&lt;li&gt;Help identify and support opportunities for collaboration with other teams across Anthropic&lt;/li&gt;
&lt;li&gt;Communicate team updates and results to other teams and leadership&lt;/li&gt;
&lt;li&gt;Maintain a deep understanding of the team&#39;s technical work and its implications for AI safety&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Are an experienced manager (minimum 2-5 years) with a track record of effectively leading highly technical research and/or engineering teams&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Have a background in machine learning, AI, or a related technical field&lt;/li&gt;
&lt;li&gt;Actively enjoy people management and are experienced with coaching and mentorship, performance evaluation, career development, and hiring for technical roles&lt;/li&gt;
&lt;li&gt;Have strong project management skills, including prioritization and cross-functional coordination and collaboration&lt;/li&gt;
&lt;li&gt;Have managed technical teams through periods of ambiguity and change&lt;/li&gt;
&lt;li&gt;Are a quick learner, capable of understanding and contributing to discussions on complex technical topics and are motivated to learn about our research&lt;/li&gt;
&lt;li&gt;Are a strong communicator both in speaking and in writing&lt;/li&gt;
&lt;li&gt;Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Experience scaling engineering infrastructure&lt;/li&gt;
&lt;li&gt;Experience working on open-ended, exploratory research agendas aimed at foundational insights&lt;/li&gt;
&lt;li&gt;Some familiarity with our work and mechanistic interpretability&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Role Specific Location Policy:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;This role is expected to be in our SF office for 3 days a week.&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$340,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$425,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

 Research Manager, Interpretability

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;
&lt;h2&gt;About the role:&lt;/h2&gt;
&lt;/div&gt;
&lt;div&gt;
&lt;p&gt;When you see what modern language models are capable of, do you wonder, &quot;How do these things work? How can we trust them?&quot;&lt;/p&gt;
&lt;p&gt;The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;People mean many different things by &quot;interpretability&quot;. We&#39;re focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do &quot;biology&quot; or &quot;neuroscience&quot; of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we&#39;re trying to &quot;reverse engineer&quot;.&lt;/p&gt;
&lt;p&gt;&amp;nbsp;A few places to learn more about our work and team at a high level are &lt;a href=&quot;https://www.youtube.com/watch?v=TxhhMTOTMDg&quot;&gt;this introduction to Interpretability&lt;/a&gt; from our research lead, &lt;a href=&quot;https://colah.github.io/about.html&quot;&gt;Chris Olah&lt;/a&gt;; a &lt;a href=&quot;https://open.spotify.com/episode/5UF79Uu94ia0fwC32a89LU&quot;&gt;discussion of our work&lt;/a&gt; on the &lt;a href=&quot;https://www.nytimes.com/column/hard-fork&quot;&gt;Hard Fork podcast&lt;/a&gt; produced by the New York Times, and this &lt;a href=&quot;https://www.anthropic.com/research/engineering-challenges-interpretability&quot;&gt;blog post&lt;/a&gt; (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team&#39;s notable publications include &lt;a href=&quot;https://transformer-circuits.pub/2021/framework/index.html&quot;&gt;A Mathematical Framework for Transformer Circuits&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2022/in-context-learning-and-induction-heads/index.html&quot;&gt;In-context Learning and Induction Heads&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot;&gt;Toy Models of Superposition&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2024/scaling-monosemanticity/&quot;&gt;Scaling Monosemanticity&lt;/a&gt;, and our Circuits’ &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/methods.html&quot;&gt;Methods&lt;/a&gt; and &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/biology.html&quot;&gt;Biology&lt;/a&gt; papers. This work builds on ideas from members&#39; work prior to Anthropic such as the &lt;a href=&quot;https://distill.pub/2020/circuits/&quot;&gt;original circuits thread&lt;/a&gt;, &lt;a href=&quot;https://distill.pub/2021/multimodal-neurons/&quot;&gt;Multimodal Neurons&lt;/a&gt;, &lt;a href=&quot;https://distill.pub/2019/activation-atlas/&quot;&gt;Activation Atlases&lt;/a&gt;, and &lt;a href=&quot;https://distill.pub/2018/building-blocks/&quot;&gt;Building Blocks&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;We aim to create a solid foundation for mechanistically understanding neural networks and making them safe (see our &lt;a href=&quot;https://transformer-circuits.pub/2023/interpretability-dreams/index.html&quot;&gt;vision post&lt;/a&gt;). In the short term, we have focused on resolving the issue of &quot;superposition&quot; (see &lt;a href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot;&gt;Toy Models of Superposition&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2023/toy-double-descent/index.html&quot;&gt;Superposition, Memorization, and Double Descent&lt;/a&gt;, and our &lt;a href=&quot;https://transformer-circuits.pub/2023/may-update/index.html&quot;&gt;May 2023 update&lt;/a&gt;), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent &lt;a href=&quot;https://www.anthropic.com/news/mapping-mind-language-model&quot;&gt;work&lt;/a&gt; found millions of features in Sonnet, one of our production language models, represents progress in this direction. In our most recent work, we develop methods that allow us to build circuits using features and use this circuits to understand the mechanisms associated with a model&#39;s computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks.&lt;/p&gt;
&lt;p&gt;We often collaborate with teams across Anthropic, such as Alignment Science and Societal Impacts to use our work to make Anthropic’s models safer. We also have an &lt;a href=&quot;https://transformer-circuits.pub/2024/april-update/index.html#interpretability-architecture&quot;&gt;Interpretability Architectures project&lt;/a&gt; that involves collaborating with Pretraining.&lt;/p&gt;
&lt;/div&gt;
&lt;div&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;h2&gt;Responsibilities:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Implement and analyze research experiments, both quickly in toy scenarios and at scale in large models&lt;/li&gt;
&lt;li&gt;Set up and optimize research workflows to run efficiently and reliably at large scale&lt;/li&gt;
&lt;li&gt;Build tools and abstractions to support rapid pace of research experimentation&lt;/li&gt;
&lt;li&gt;Develop and improve tools and infrastructure to support other teams in using Interpretability’s work to improve model safety&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;h2&gt;You may be a good fit if you:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 5-10+ years of experience building software&lt;/li&gt;
&lt;li&gt;Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with python&lt;/li&gt;
&lt;li&gt;Have some experience contributing to empirical AI research projects&lt;/li&gt;
&lt;li&gt;Have a strong ability to prioritize and direct effort toward the most impactful work and are comfortable operating with ambiguity and questioning assumptions.&lt;/li&gt;
&lt;li&gt;Prefer fast-moving collaborative projects to extensive solo efforts&lt;/li&gt;
&lt;li&gt;Want to learn more about machine learning research and its applications and collaborate closely with researchers&lt;/li&gt;
&lt;li&gt;Care about the societal impacts and ethics of your work&lt;/li&gt;
&lt;/ul&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;h2&gt;Strong candidates may also have experience with:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Designing a code base so that anyone can quickly code experiments, launch them, and analyze their results without hitting bugs&lt;/li&gt;
&lt;li&gt;Optimizing the performance of large-scale distributed systems&lt;/li&gt;
&lt;li&gt;Collaborating closely with researchers&lt;/li&gt;
&lt;li&gt;Language modeling with transformers&lt;/li&gt;
&lt;li&gt;GPUs or Pytorch&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;h2&gt;Representative Projects:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Building &lt;a href=&quot;https://transformer-circuits.pub/2021/garcon/index.html&quot;&gt;Garcon&lt;/a&gt;, a tool that allows researchers to easily access LLMs internals from a jupyter notebook&lt;/li&gt;
&lt;li&gt;Setting up and optimizing a pipeline to efficiently collect petabytes of transformer activations and shuffle them.&lt;/li&gt;
&lt;li&gt;Profiling and optimizing ML training, including parallelizing to many GPUs&lt;/li&gt;
&lt;li&gt;Make launching ML experiments and manipulating+analyzing the results fast and easy&lt;/li&gt;
&lt;li&gt;Creating an interactive visualization of attention between tokens in a language model&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Role Specific Location Policy:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;This role is based in San Francisco office; however, we are open to considering exceptional candidates for remote work on a case-by-case basis.&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;
&lt;/div&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$315,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$560,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Research Engineer, Interpretability

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;About the role&lt;/h2&gt;
&lt;p&gt;We are looking for a Machine Learning Engineer to help us train Claude specifically for virtual collaborator workflows. While Claude excels at general tasks, a lot of knowledge work requires targeted training on real organizational data and workflows. Your job will be to design and implement reinforcement learning environments that transform Claude into the best virtual collaborator, training on everything from navigating internal knowledge to creating financial models.&lt;/p&gt;
&lt;h2&gt;Responsibilities:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Designing and implementing reinforcement learning pipelines specifically targeted at virtual collaborator use cases (productivity, organizational navigation, vertical domains)&lt;/li&gt;
&lt;li&gt;Building and scaling our data creation platform for generating high-quality, open-ended tasks with domain experts and crowdworkers Integrating real organizational data to create authentic training environments&lt;/li&gt;
&lt;li&gt;Developing robust rubric-based evaluation systems that maintain quality while avoiding reward hacking&lt;/li&gt;
&lt;li&gt;Training Claude on advanced document manipulation, including understanding, enhancing, and co-creating&lt;/li&gt;
&lt;li&gt;Partnering directly with product teams to ensure training aligns with shipped features&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;You may be a good fit if you:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using&lt;/li&gt;
&lt;li&gt;Have strong machine learning experience&lt;/li&gt;
&lt;li&gt;Thrive at the intersection of research and product, with a pragmatic approach to solving real-world problems&lt;/li&gt;
&lt;li&gt;Are comfortable with ambiguity and can balance research rigor with shipping deadlines&lt;/li&gt;
&lt;li&gt;Enjoy collaborating across multiple teams (data operations, model training, product)&lt;/li&gt;
&lt;li&gt;Can context-switch between research problems and product engineering tasks&lt;/li&gt;
&lt;li&gt;Care about making AI genuinely helpful for everyday enterprise workflows&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;Strong candidates may also have experience with:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Building human-in-the-loop training systems or crowdsourcing platforms&lt;/li&gt;
&lt;li&gt;Working with enterprise tools and APIs (Google Workspace, Microsoft Office, Slack, etc.)&lt;/li&gt;
&lt;li&gt;Developing evaluation frameworks for open-ended tasks&lt;/li&gt;
&lt;li&gt;Domain expertise in finance, legal, or healthcare workflows&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Creating scalable data pipelines with quality control mechanisms&lt;/li&gt;
&lt;li&gt;Reward modeling and preventing reward hacking in RL systems&lt;/li&gt;
&lt;li&gt;Translating product requirements into technical training objectives&amp;nbsp;&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Deadline to apply:&amp;nbsp;&lt;/strong&gt;None. Applications will be reviewed on a rolling basis.&amp;nbsp;&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$340,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$560,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Staff Machine Learning Engineer, Virtual Collaborator

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;
&lt;div&gt;
&lt;h2&gt;About the role:&lt;/h2&gt;
&lt;/div&gt;
&lt;div&gt;
&lt;p&gt;Agentic systems are the next frontier of usefulness for Claude.&amp;nbsp; Over the last year, we’ve seen rapid adoption of Claude-powered agentic systems in spaces like coding, research, customer support, network security, and more. We believe this is just the beginning, and we expect Claude to be handling much more complex tasks end-to-end or in cooperation with a human user as time goes on.&amp;nbsp; We have a team striving to make Claude an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, memory, and inter-agent coordination. This team endeavors to maximize agent performance by solving challenges at whatever level is needed, whether it’s finetuning, agent infrastructure, or agent design best practices.&lt;/p&gt;
&lt;p&gt;Given that this is a nascent field, we ask that you share with us a project built on LLMs that showcases your skill at getting them to do complex tasks. Here are some example projects of interest: design of complex agents, quantitative experiments with prompting, constructing model benchmarks, synthetic data generation, model finetuning, or application of LLMs to a complex task. There is no preferred task; we just want to see what you can build. It’s fine if several people worked on it; simply share what part of it was your contribution. You can also include a short description of the process you used or any roadblocks you hit and how to deal with them, but this is not a requirement.&lt;/p&gt;
&lt;h3&gt;&amp;nbsp;&lt;/h3&gt;
&lt;h3&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Finetune new capabilities into Claude that maximize Claude’s performance or ease of use on agentic tasks&lt;/li&gt;
&lt;li&gt;Ideate, develop, and compare the performance of different tools for agents&amp;nbsp; (eg memory, context compression, communication architectures for agents)&lt;/li&gt;
&lt;li&gt;Systematically discover and test prompt engineering best practices for agents&lt;/li&gt;
&lt;li&gt;Develop automated techniques for designing and evaluating agentic systems&lt;/li&gt;
&lt;li&gt;Assist with automated evaluation of Claude models and prompts across the training and product lifecycle&lt;/li&gt;
&lt;li&gt;Work with our product org to find solutions to our most vexing challenges applying agents to our products&lt;/li&gt;
&lt;li&gt;Help create and optimize data mixes for model training&lt;/li&gt;
&lt;li&gt;Help to create and maintain the infrastructure required for efficient prompt iteration and testing.&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Have 7+ years of ML and software engineering experience&lt;/li&gt;
&lt;li&gt;Have at least a high level familiarity with the architecture and operation of large language models&lt;/li&gt;
&lt;li&gt;Have extensive prior experience exploring and testing language model behavior&lt;/li&gt;
&lt;li&gt;Have spent time prompting and/or building products with language models&lt;/li&gt;
&lt;li&gt;Have good communication skills and an interest in working with other researchers on difficult tasks&lt;/li&gt;
&lt;li&gt;Have a passion for making powerful technology safe and societally beneficial&lt;/li&gt;
&lt;li&gt;Stay up-to-date and informed by taking an active interest in emerging research and industry trends.&lt;/li&gt;
&lt;li&gt;Enjoy pair programming (we love to pair!)&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Strong candidates may also have experience with:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Developing complex agentic systems using LLMs&lt;/li&gt;
&lt;li&gt;Large-scale RL on language models&lt;/li&gt;
&lt;li&gt;Multi-agent systems&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Representative projects:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Implementing and testing a novel retrieval, tool use, sub-agent, or memory architecture for Claude&lt;/li&gt;
&lt;li&gt;Finetuning Claude to maximize its performance using a particular set of agent tools (eg a read-write memory, or an inter-agent communication system)&lt;/li&gt;
&lt;li&gt;Building the prompting and model orchestration for a production application backed by a language model&lt;/li&gt;
&lt;li&gt;Building and testing an automatic prompt optimizer or automatic LLM-driven evaluation system for judging a prompt’s performance on a task.&lt;/li&gt;
&lt;li&gt;Building a scaled model evaluation framework driven by model-based evaluation techniques.&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;/div&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$340,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$560,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Staff Machine Learning Engineer, Agent Skills

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic&#39;s Infrastructure team is seeking a Data Center Energy Lead to secure power capacity and accelerate energy delivery for our rapidly expanding AI compute footprint. You&#39;ll work at the intersection of energy markets, utility operations, and AI infrastructure needs, leading multi-hundred megawatt procurement efforts and building strategic relationships with utilities, grid operators, and regulators across multiple jurisdictions. This role is essential to ensuring Anthropic can scale compute capacity efficiently while navigating complex energy market dynamics and regulatory environments to achieve the speed and scale required for frontier AI development.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Lead energy procurement and markets strategy to secure multi-hundred megawatt power capacity for AI infrastructure, structuring utility partnerships and commercial agreements that prioritize speed-to-energization and scale&lt;/li&gt;
&lt;li&gt;Own utility and regulatory stakeholder management across multiple jurisdictions, building strategic relationships with ISOs, transmission operators, and utilities to accelerate interconnection timelines and unlock constrained capacity&lt;/li&gt;
&lt;li&gt;Drive energy markets and policy strategy for AI compute facilities, monitoring regulatory developments and engaging policymakers to address grid capacity challenges and expedite approval processes for critical infrastructure&lt;/li&gt;
&lt;li&gt;Partner with engineering and delivery teams to translate energy market dynamics and utility constraints into actionable capacity acceleration strategies that align procurement schedules with aggressive project timelines&lt;/li&gt;
&lt;li&gt;Develop deep market intelligence on regional power availability, transmission constraints, and interconnection queue dynamics to inform site selection and deployment strategy&lt;/li&gt;
&lt;li&gt;Structure innovative commercial frameworks and partnership models that enable faster power delivery and mitigate grid capacity risks across Anthropic&#39;s datacenter portfolio&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 7+ years of experience in energy procurement, utility development, or power markets for large-scale infrastructure projects&lt;/li&gt;
&lt;li&gt;Have deep expertise in wholesale power markets, utility interconnection processes, and transmission system planning&lt;/li&gt;
&lt;li&gt;Have experience securing 100+ MW of power capacity and navigating complex utility service agreements or power purchase agreements&lt;/li&gt;
&lt;li&gt;Are proficient in analyzing energy market dynamics, regulatory frameworks, and grid constraints to inform strategic decision-making&lt;/li&gt;
&lt;li&gt;Have strong stakeholder management skills and experience building relationships with utilities, ISOs/RTOs, regulators, and policymakers&lt;/li&gt;
&lt;li&gt;Have excellent communication skills and can translate complex grid and regulatory dynamics into actionable business strategies for technical and non-technical audiences&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have some of the following:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Past experience with energy procurement specifically for datacenters, high-performance computing, or AI/ML infrastructure&lt;/li&gt;
&lt;li&gt;Familiarity with hyperscale infrastructure requirements and the unique power demands of large-scale AI training and inference workloads&lt;/li&gt;
&lt;li&gt;Experience with regulatory affairs, energy policy advocacy, or engagement with state/federal energy commissions (FERC, state PUCs)&lt;/li&gt;
&lt;li&gt;Background in transmission planning, interconnection study processes, or grid capacity analysis&lt;/li&gt;
&lt;li&gt;Understanding of emerging grid technologies (energy storage, demand response, distributed energy resources) and how they can accelerate capacity delivery&lt;/li&gt;
&lt;li&gt;Track record of structuring creative solutions to overcome grid constraints and compressed timelines in competitive power markets&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$1&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$2 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Data Center Energy Lead

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We are seeking a Finance AI Solutions Engineer to help build the next generation of AI-powered tools for finance and accounting teams. You&#39;ll work at the intersection of engineering, product development, and finance operations, collaborating closely with our Finance team to transform how finance professionals interact with data and automate their workflows using Claude.&lt;/p&gt;
&lt;p&gt;This role offers the opportunity to take full ownership of complex problems at the frontier of AI application in finance. You&#39;ll rapidly build proof-of-concepts that demonstrate value, working with passionate engineers and stakeholders to architect and implement innovative solutions. Your work will span both internal tools for Anthropic&#39;s finance team and insights that inform external products, directly contributing to our mission of building safe and beneficial AI systems.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Build AI-powered prototypes that showcase how Claude can solve real finance and accounting problems - from document processing to natural language data queries&lt;/li&gt;
&lt;li&gt;Design and implement systems that handle OCR, document parsing, and natural language processing to transform unstructured finance data into actionable insights&lt;/li&gt;
&lt;li&gt;Partner closely with accounting and finance teams to understand workflows, pain points, and requirements, then translate those into technical specifications and working prototypes&lt;/li&gt;
&lt;li&gt;Build and maintain data pipelines, manage metadata, and ensure the underlying data infrastructure supports reliable AI applications&lt;/li&gt;
&lt;li&gt;Work with product teams to shape the roadmap and ensure what you&#39;re building is supported on the platform&lt;/li&gt;
&lt;li&gt;Iterate rapidly from concept to working prototype, gather feedback from finance users, and refine based on what you learn&lt;/li&gt;
&lt;li&gt;Identify opportunities to automate manual finance processes through AI technologies and system integration&lt;/li&gt;
&lt;li&gt;Create technical documentation and provide guidance to finance teams on how to leverage AI tools effectively&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have strong software engineering fundamentals and ability to build end-to-end applications&lt;/li&gt;
&lt;li&gt;Have experience with natural language processing, document processing (OCR), or working with unstructured data&lt;/li&gt;
&lt;li&gt;Are comfortable with data engineering: pipelines, data quality, metadata management, ETL processes&lt;/li&gt;
&lt;li&gt;Have ability to work closely with non-technical stakeholders and translate business needs into technical solutions&lt;/li&gt;
&lt;li&gt;Have a track record of building prototypes or MVPs quickly and iteratively in fast-paced environments&lt;/li&gt;
&lt;li&gt;Possess strong analytical and problem-solving skills with the ability to take ownership of complex problems&lt;/li&gt;
&lt;li&gt;Have excellent communication skills and can effectively collaborate with both technical and business stakeholders&lt;/li&gt;
&lt;li&gt;Are excited about AI&#39;s potential to transform knowledge work and care about building systems that are safe and beneficial&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Experience building tools for finance or accounting teams&lt;/li&gt;
&lt;li&gt;Familiarity with financial data structures, accounting systems, or ERP platforms&lt;/li&gt;
&lt;li&gt;Experience with LLMs, prompt engineering, and AI application development&lt;/li&gt;
&lt;li&gt;Background in data warehousing or analytics platforms (BigQuery, Snowflake, etc.)&lt;/li&gt;
&lt;li&gt;Prior work on internal tools that scaled to external products&lt;/li&gt;
&lt;li&gt;Experience with financial processes including close, reporting, and compliance workflows&lt;/li&gt;
&lt;li&gt;Knowledge of modern cloud-based finance platforms and integrations&lt;/li&gt;
&lt;li&gt;Understanding of startup financial operations and scaling challenges&lt;/li&gt;
&lt;li&gt;Experience in technology companies or other high-growth environments&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$205,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$265,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Finance Systems, AI Data Engineer

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We&#39;re looking for experienced engineers to build and scale the database infrastructure that powers both Claude&#39;s product offerings and Anthropic&#39;s research initiatives. As a Staff Software Engineer on the Infrastructure team, you will architect and operate database systems that both enable millions of users to interact with Claude and support cutting-edge AI research.&lt;/p&gt;
&lt;p&gt;This is a unique opportunity to tackle database challenges at unprecedented scale. You&#39;ll develop the database strategy for Anthropic, design systems that handle billions of API requests, create storage solutions that work seamlessly across GCP, AWS, and diverse deployment models, and build the reliable data layer that accelerates research experimentation.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Set the technical direction for database solutions used across Product and Research&lt;/li&gt;
&lt;li&gt;Design and implement database solutions that scale to support millions of users across Claude&#39;s product ecosystem&lt;/li&gt;
&lt;li&gt;Build and scale database systems through 100x+ growth while maintaining reliability and performance&lt;/li&gt;
&lt;li&gt;Architect data storage solutions that work seamlessly across GCP, AWS, first-party deployments, third-party deployments, and other environments&lt;/li&gt;
&lt;li&gt;Develop database infrastructure that serves both product and research workloads with different performance characteristics&lt;/li&gt;
&lt;li&gt;Partner with product and research teams to understand data requirements and build infrastructure that accelerates innovation&lt;/li&gt;
&lt;li&gt;Optimize database performance, reliability, and cost efficiency at massive scale&lt;/li&gt;
&lt;li&gt;Make critical build vs. buy decisions for database technologies&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You might be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 8+ years of experience building and scaling database systems&lt;/li&gt;
&lt;li&gt;Possess deep expertise in distributed database architectures and OLTP systems at scale&lt;/li&gt;
&lt;li&gt;Have successfully scaled databases through massive growth at high-growth companies&lt;/li&gt;
&lt;li&gt;Can balance the speed of a startup environment with the reliability needs of production systems&lt;/li&gt;
&lt;li&gt;Excel at technical leadership and cross-functional collaboration&lt;/li&gt;
&lt;li&gt;Are passionate about building the data layer that enables next-generation AI capabilities&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Deep expertise scaling PostgreSQL, MySQL, DynamoDB, or similar database systems&lt;/li&gt;
&lt;li&gt;Experience with Redis, Temporal, vector databases, or async job processing frameworks&lt;/li&gt;
&lt;li&gt;Experience building multi-cloud or hybrid cloud database solutions&lt;/li&gt;
&lt;li&gt;Knowledge of database orchestration and automation at scale&lt;/li&gt;
&lt;li&gt;Background at companies known for database excellence&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Note: Prior AI/ML infrastructure experience is not required. We value deep infrastructure/databases expertise from any domain.&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$405,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$485,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Staff+ Software Engineer - Databases

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by establishing robust analytics engineering and business intelligence capabilities for our Accounting organization. In this unique company, technology, and moment in history, your work will be critical to ensuring accurate financial reporting, streamlining accounting processes, and supporting our financial operations as we deploy safe, frontier AI at scale to the world.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;In your role, you will use advanced analytics to drive strategic decision-making and sound operations for our accounting teams. You&#39;ll work at the intersection of finance, analytics, and business intelligence to develop automated reporting systems, data quality frameworks, and scaled insights that support our various business models and entities. You’ll partner closely with Data Infrastructure, Finance Systems, and the Accounting organization: Corporate Accounting, Revenue Accounting, Technical Accounting, International Accounting, and Finance Operations (FinOps). You&#39;ve worked in cultures of excellence in the past and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;Establish the foundation for accounting analytics and BI at Anthropic, creating processes and best practices for financial data management, governance, and reporting&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Build and maintain automated financial reporting systems, dashboards, and solutions that provide real-time insights to accounting and finance leadership&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Develop sophisticated revenue recognition analytics and monitoring to support our subscription- and consumption-based business model&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Partner with Accounting teams (Corporate, International, Technical, Revenue, FinOps) to streamline close processes and financial reporting&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Design and implement audit support systems and documentation processes to facilitate external audits and compliance requirements&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Partner with Data Infrastructure, Analytics Engineering, and Financial Systems teams to develop scalable data pipelines and infrastructure supporting accounting analytics&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Champion data-informed decision making across the organization&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 class=&quot;heading&quot;&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;Have 8+ years of experience in finance analytics, business intelligence, or financial systems analysis with demonstrated experience partnering with Accounting, Data Infrastructure, and Financial Systems teams&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Are highly proficient in SQL and Python for data manipulation, analysis, and automation&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Have extensive experience with BI visualization tools such as Looker or Tableau; and have experience with cloud platforms (AWS, GCP) and modern data stack tools (dbt, Airflow, etc.)&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Have hands-on experience working with financial systems like NetSuite, Stripe, or other ERP/financial platforms, and building downstream data models from these systems&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Possess strong financial acumen with deep understanding of accounting principles (GAAP vs. non-GAAP, revenue recognition, SOX), financial statements, and corporate finance processes&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Have a proven track record of collaborating with finance stakeholders to deliver impactful analytical solutions and process improvements&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Excel at translating complex business requirements into technical solutions and can communicate effectively with both technical and non-technical stakeholders&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Are detail-oriented with a commitment to data accuracy and have experience building robust, scalable analytical solutions&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Thrive in fast-paced environments and can manage multiple priorities while maintaining high-quality deliverables&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Have experience with data modeling, ETL processes, and building automated reporting solutions&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 class=&quot;heading&quot;&gt;&lt;strong&gt;Strong candidates may have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;
&lt;p&gt;Relevant certifications in financial systems or business intelligence platforms&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Prior experience in high-growth technology companies or startups&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Knowledge of statistical analysis and advanced analytics techniques&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Experience with financial planning and analysis (FP&amp;amp;A) processes and systems&lt;/p&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;p&gt;Familiarity with data governance best practices and experience implementing data quality frameworks&lt;/p&gt;
&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$265,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$315,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Finance Analytics & BI, Accounting

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We&#39;re looking for experienced engineers to build and scale the database infrastructure that powers both Claude&#39;s product offerings and Anthropic&#39;s research initiatives. As a Staff Software Engineer on the Infrastructure team, you will architect and operate database systems that both enable millions of users to interact with Claude and support cutting-edge AI research.&lt;/p&gt;
&lt;p&gt;This is a unique opportunity to tackle database challenges at unprecedented scale. You&#39;ll develop the database strategy for Anthropic, design systems that handle billions of API requests, create storage solutions that work seamlessly across GCP, AWS, and diverse deployment models, and build the reliable data layer that accelerates research experimentation.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Set the technical direction for database solutions used across Product and Research&lt;/li&gt;
&lt;li&gt;Design and implement database solutions that scale to support millions of users across Claude&#39;s product ecosystem&lt;/li&gt;
&lt;li&gt;Build and scale database systems through 100x+ growth while maintaining reliability and performance&lt;/li&gt;
&lt;li&gt;Architect data storage solutions that work seamlessly across GCP, AWS, first-party deployments, third-party deployments, and other environments&lt;/li&gt;
&lt;li&gt;Develop database infrastructure that serves both product and research workloads with different performance characteristics&lt;/li&gt;
&lt;li&gt;Partner with product and research teams to understand data requirements and build infrastructure that accelerates innovation&lt;/li&gt;
&lt;li&gt;Optimize database performance, reliability, and cost efficiency at massive scale&lt;/li&gt;
&lt;li&gt;Make critical build vs. buy decisions for database technologies&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You might be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 8+ years of experience building and scaling database systems&lt;/li&gt;
&lt;li&gt;Possess deep expertise in distributed database architectures and OLTP systems at scale&lt;/li&gt;
&lt;li&gt;Have successfully scaled databases through massive growth at high-growth companies&lt;/li&gt;
&lt;li&gt;Can balance the speed of a startup environment with the reliability needs of production systems&lt;/li&gt;
&lt;li&gt;Excel at technical leadership and cross-functional collaboration&lt;/li&gt;
&lt;li&gt;Are passionate about building the data layer that enables next-generation AI capabilities&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Deep expertise scaling PostgreSQL, MySQL, DynamoDB, or similar database systems&lt;/li&gt;
&lt;li&gt;Experience with Redis, Temporal, vector databases, or async job processing frameworks&lt;/li&gt;
&lt;li&gt;Experience building multi-cloud or hybrid cloud database solutions&lt;/li&gt;
&lt;li&gt;Knowledge of database orchestration and automation at scale&lt;/li&gt;
&lt;li&gt;Background at companies known for database excellence&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Note: Prior AI/ML infrastructure experience is not required. We value deep infrastructure/databases expertise from any domain.&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$320,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$485,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Staff+ Software Engineer, Databases

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;
&lt;h3&gt;&lt;strong&gt;About the Role&lt;/strong&gt;&lt;/h3&gt;
&lt;p&gt;Data Infrastructure designs, operates, and scales secure, privacy-respecting systems that power data-driven decisions across Anthropic. Our mission is to provide data processing, storage, and access that are trusted, fast, and easy to use.&lt;/p&gt;
&lt;p&gt;We&#39;re looking for infrastructure engineers who thrive working at the intersection of data systems, security, and scalability. You&#39;ll tackle diverse challenges ranging from building financial reporting pipelines to architecting access control systems to ensuring cloud storage reliability. This role offers the opportunity to work directly with data scientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives.&lt;/p&gt;
&lt;h3&gt;&lt;strong&gt;What You&#39;ll Work On&lt;/strong&gt;&lt;/h3&gt;
&lt;p&gt;Depending on your background and interests, you may focus on areas such as:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Data Governance &amp;amp; Access Control&lt;/strong&gt;: Design and implement robust access control systems ensuring only authorized users can access sensitive data. Build infrastructure for permission management, audit logging, and compliance requirements. Work on IAM policies, ACLs, and security controls that scale across thousands of users and systems.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Financial Data Infrastructure&lt;/strong&gt;: Build and maintain data pipelines and warehouses powering business-critical reporting. Ensure data integrity, accuracy, and availability for complex financial systems, including third party revenue ingestion pipelines; manage the external relationships as needed to drive upstream dependencies. Own the reliability of systems processing revenue, usage, and business metrics.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Cloud Storage &amp;amp; Reliability&lt;/strong&gt;: Architect disaster recovery, backup, and replication systems for petabyte-scale data. Ensure high availability and durability of data stored in cloud object storage (GCS, S3). Build systems that protect against data loss and enable rapid recovery.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Data Platform &amp;amp; Tooling&lt;/strong&gt;: Scale data processing infrastructure using technologies like BigQuery, BigTable, Airflow, dbt, and Spark. Optimize query performance, manage costs, and enable self-service analytics across the organization.&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;You May Be a Good Fit If You:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Have 8+ years of software engineering experience with 3+ years building data infrastructure, storage systems, or related distributed systems&lt;/li&gt;
&lt;li&gt;Have deep experience with at least one of:&lt;/li&gt;
&lt;ul&gt;
&lt;li&gt;Cloud data platforms (BigQuery, Redshift, Snowflake) and orchestration tools (Airflow, dbt)&lt;/li&gt;
&lt;li&gt;Access control systems, IAM, authentication/authorization at scale&lt;/li&gt;
&lt;li&gt;Distributed storage systems, object storage (S3, GCS), disaster recovery&lt;/li&gt;
&lt;/ul&gt;
&lt;li&gt;Strong proficiency in programming languages like Python, Go, Java, or similar&lt;/li&gt;
&lt;li&gt;Experience with infrastructure-as-code (Terraform, Pulumi) and cloud platforms (GCP, AWS)&lt;/li&gt;
&lt;li&gt;Can navigate complex technical tradeoffs between performance, cost, security, and maintainability&lt;/li&gt;
&lt;li&gt;Have excellent collaboration skills - you work well with both technical and non-technical stakeholders&lt;/li&gt;
&lt;li&gt;Are comfortable with ambiguity and can independently scope and drive large projects&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Strong Candidates May Also Have:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Experience with security and compliance requirements (ITGC, GDPR, financial controls)&lt;/li&gt;
&lt;li&gt;Background in data warehousing, ETL/ELT pipelines, or analytics infrastructure&lt;/li&gt;
&lt;li&gt;Experience with Kubernetes, containerization, and cloud-native architectures&lt;/li&gt;
&lt;li&gt;Track record of improving data reliability, availability, or cost efficiency at scale&lt;/li&gt;
&lt;li&gt;Knowledge of column-oriented databases, OLAP systems, or big data processing frameworks&lt;/li&gt;
&lt;li&gt;Experience working in fintech, financial services, or highly regulated environments&lt;/li&gt;
&lt;li&gt;Security engineering background with focus on data protection and access controls&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Technologies We Use:&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Data: BigQuery, BigTable, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran&lt;/li&gt;
&lt;li&gt;Storage: GCS, S3&lt;/li&gt;
&lt;li&gt;Infrastructure: Terraform, Kubernetes, GCP, AWS&lt;/li&gt;
&lt;li&gt;Languages: Python, Go, SQL&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;p&gt;&lt;strong&gt;Deadline to apply:&amp;nbsp;&lt;/strong&gt;None. Applications will be reviewed on a rolling basis.&amp;nbsp;&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$405,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$485,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Staff+ Software Engineer - Data Infrastructure

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the Role&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Join Anthropic&#39;s Legal Operations team as we scale to support one of the world&#39;s leading AI companies. As a Legal Operations Specialist, you&#39;ll be the operational backbone ensuring our legal team has the tools, vendor relationships, and financial processes needed to deliver exceptional legal support to the business. You&#39;ll manage critical platforms and coordinate with internal and external partners while optimizing costs and streamlining processes. This role offers the opportunity to build scalable operations from the ground up in a fast-paced, mission-driven environment focused on AI safety and responsible development.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Manage day-to-day operations of Brightflag billing platform, including matter setup, user management, and billing workflow optimization&lt;/li&gt;
&lt;li&gt;Serve as primary liaison with outside counsel on billing inquiries, invoice processing, and administrative coordination across all practice areas&lt;/li&gt;
&lt;li&gt;Handle monthly financial accruals and budget tracking, collaborating with Finance team on forecast updates and cost optimization initiatives&lt;/li&gt;
&lt;li&gt;Lead renewal processes for critical legal tools including DocuSign, Westlaw, Law360, PLI, and LSuite, ensuring optimal pricing and feature alignment&lt;/li&gt;
&lt;li&gt;Execute end-to-end vendor management including vendor onboarding, contract negotiations, relationship management, and performance monitoring&lt;/li&gt;
&lt;li&gt;Maintain comprehensive forecast trackers and provide analytical insights to support budget planning and cost management decisions&lt;/li&gt;
&lt;li&gt;Coordinate with IT and other teams to ensure seamless integration of legal operations tools with broader company systems&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have at least 5 years of experience in legal operations, professional services operations, or similar vendor/billing management roles&lt;/li&gt;
&lt;li&gt;Demonstrate strong analytical skills with experience in financial tracking, budget management, and cost optimization&lt;/li&gt;
&lt;li&gt;Possess excellent communication skills and can effectively manage relationships with external vendors and internal stakeholders&lt;/li&gt;
&lt;li&gt;Show proficiency with SaaS platforms and ability to quickly learn new systems and tools&lt;/li&gt;
&lt;li&gt;Have experience with vendor management processes including contract negotiation, onboarding, and relationship management&lt;/li&gt;
&lt;li&gt;Are detail-oriented with strong project management skills and ability to handle multiple competing priorities&lt;/li&gt;
&lt;li&gt;Thrive in fast-paced, high-growth environments and can adapt quickly to changing business needs&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Previous experience with legal billing platforms (Brightflag, Legal Tracker, or similar) or legal practice management systems&lt;/li&gt;
&lt;li&gt;Background in legal operations at law firms or corporate legal departments with exposure to outside counsel management&lt;/li&gt;
&lt;li&gt;Experience with financial analysis, budgeting, and working closely with Finance teams in a business operations capacity&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Role-specific policy:&lt;/strong&gt; For this role, we expect all staff to be able to work from our San Francisco office at least 3 days a week, though we encourage you to apply even if you might need some flexibility for an interim period of time.&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$170,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$220,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Legal Operations Specialist, Billing

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We are seeking a talented Analytics lead to join our Recruiting Analytics team at Anthropic. In this role, you will transform data into actionable insights that drive strategic decision-making across our rapidly growing organization. You&#39;ll work closely with leadership and cross-functional teams to identify trends, measure performance, and optimize our people practices as we scale our mission-critical work in AI safety.&lt;/p&gt;
&lt;p&gt;As a key member of our data-driven culture, you&#39;ll help ensure that our talent strategies are grounded in evidence and aligned with our goal of building reliable, interpretable, and steerable AI systems. This role offers the opportunity to make a significant impact on how we attract, develop, and retain the exceptional talent needed to advance AI safety.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Data Analysis &amp;amp; Insights&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Analyze complex datasets to identify trends, patterns, and opportunities across the employee lifecycle&lt;/li&gt;
&lt;li&gt;Conduct rigorous statistical analysis to support evidence-based decision-making for talent management initiatives&lt;/li&gt;
&lt;li&gt;Perform root cause analysis on people-related metrics to understand underlying drivers of organizational outcomes&lt;/li&gt;
&lt;li&gt;Design and execute research projects that advance our understanding of what drives employee success and satisfaction&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Visualization &amp;amp; Communication&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Come up with creative solutions to displaying data (going beyond the traditional dashboard, leveraging AI etc.)&lt;/li&gt;
&lt;li&gt;At the same time, create and maintain interactive dashboards and visualizations that help communicate complex data insights to key stakeholders&lt;/li&gt;
&lt;li&gt;Translate complex data analyses into clear, compelling narratives for both technical and non-technical audiences&lt;/li&gt;
&lt;li&gt;Convert insights into actionable recommendations and drive implementation of solutions&lt;/li&gt;
&lt;li&gt;Collaborate with company leaders to identify, track, and iterate key performance indicators (KPIs) for talent management&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Cross-Functional Partnerships&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Partner with stakeholders to define and scope people analytics projects that align with organizational goals&lt;/li&gt;
&lt;li&gt;Work directly with executives to understand business challenges and translate them into technical solutions&lt;/li&gt;
&lt;li&gt;Advise on best practices for integrating and analyzing data from various HR systems (e.g., Workday, ATS, surveys) and external sources&lt;/li&gt;
&lt;li&gt;Take ownership of diverse responsibilities from research projects to operational process implementation, root cause analysis, and program management&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Data Infrastructure &amp;amp; Operations&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Model downstream tables for custom reporting and analytics.&lt;/li&gt;
&lt;li&gt;Ensure data quality and integrity across recruiting analytics systems and processes&lt;/li&gt;
&lt;li&gt;Develop and maintain automated reporting solutions that scale with organizational growth&lt;/li&gt;
&lt;li&gt;Collaborate with engineering teams to improve data collection and storage practices&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 5+ years of experience in data analysis, preferably with recruiting analytics, people analytics, or related fields&lt;/li&gt;
&lt;li&gt;Have additional experience in people operations or recruiting.&lt;/li&gt;
&lt;li&gt;Are proficient in SQL and experienced with data visualization tools (e.g., Tableau, Looker, Looker Studio, Power BI)&lt;/li&gt;
&lt;li&gt;Are comfortable working with messy or incomplete data&lt;/li&gt;
&lt;li&gt;Have strong statistical analysis skills and experience with programming languages such as Python or R&lt;/li&gt;
&lt;li&gt;Possess excellent communication skills and can translate complex analytical findings into actionable business insights&lt;/li&gt;
&lt;li&gt;Are results-oriented with a bias towards flexibility and impact&lt;/li&gt;
&lt;li&gt;Thrive in a fast-paced, collaborative environment and enjoy working closely with cross-functional teams&lt;/li&gt;
&lt;li&gt;Have experience working with HRIS systems and people data&lt;/li&gt;
&lt;li&gt;Care about ensuring that advanced AI systems are developed safely and are passionate about our mission&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Advanced degree in Statistics, Data Science, Psychology, Economics, or related quantitative field&lt;/li&gt;
&lt;li&gt;Experience with A/B testing and experimental design&lt;/li&gt;
&lt;li&gt;Previous experience in high-growth technology companies or startups&lt;/li&gt;
&lt;li&gt;Familiarity with data privacy regulations and ethical considerations in people analytics&lt;/li&gt;
&lt;li&gt;Experience with cloud-based data platforms (AWS, GCP) and modern data stack tools&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Representative projects:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Modeling data and building dashboards to drive better decision making around Interviewer training and deeper understanding of interviewer capacity &amp;amp; capacity constraints.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Conducting research on the effectiveness of our hiring processes and recommending improvements to reduce bias and improve candidate experience&lt;/li&gt;
&lt;li&gt;Collaborate with our compensation team to developing data-driven compensation analysis to ensure pay equity and market competitiveness&lt;/li&gt;
&lt;li&gt;Work with recruiting leaders to help them report to the business on basic recruiting metrics, hiring predictions, and opportunities for improvement.&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$160,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$205,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Recruiting Data Analytics & Engineering

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the Interpretability team:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;When you see what modern language models are capable of, do you wonder, &quot;How do these things work? How can we trust them?&quot;&lt;/p&gt;
&lt;p&gt;The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;People mean many different things by &quot;interpretability&quot;. We&#39;re focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do &quot;biology&quot; or &quot;neuroscience&quot; of neural networks, or as treating neural networks as binary computer programs we&#39;re trying to &quot;reverse engineer&quot;.&lt;/p&gt;
&lt;p&gt;We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our &lt;a href=&quot;https://transformer-circuits.pub/2023/interpretability-dreams/index.html&quot;&gt;vision post&lt;/a&gt;). We have focused on resolving the issue of &quot;superposition&quot; (see &lt;a href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot;&gt;Toy Models of Superposition&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2023/toy-double-descent/index.html&quot;&gt;Superposition, Memorization, and Double Descent&lt;/a&gt;, and our &lt;a href=&quot;https://transformer-circuits.pub/2023/may-update/index.html&quot;&gt;May 2023 update&lt;/a&gt;), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent &lt;a href=&quot;https://www.anthropic.com/news/mapping-mind-language-model&quot;&gt;work&lt;/a&gt; which found millions of features in Claude 3.0 Sonnet, one of our production language models, represents progress in this direction. In our &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/methods.html&quot;&gt;most recent work&lt;/a&gt;, we developed methods that allow us to build circuits using features and use these circuits to understand the mechanisms associated with a model&#39;s computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Claude Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks.&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;A few places to learn more about our work and team are this &lt;a href=&quot;https://www.youtube.com/watch?v=TxhhMTOTMDg&quot;&gt;introduction to Interpretability&lt;/a&gt; from our research lead, &lt;a href=&quot;https://colah.github.io/about.html&quot;&gt;Chris Olah, Stanford CS25 lecture given by Josh Batson, and&lt;/a&gt; &lt;a href=&quot;https://twimlai.com/podcast/twimlai/exploring-the-biology-of-llms-with-circuit-tracing/&quot;&gt;TWIML AI podcast&lt;/a&gt; with Emmanuel Ameisen.&lt;/p&gt;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;p&gt;Some of our team&#39;s notable publications include and our Circuits’ &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/methods.html&quot;&gt;Methods&lt;/a&gt; and &lt;a href=&quot;https://transformer-circuits.pub/2025/attribution-graphs/biology.html&quot;&gt;Biology&lt;/a&gt; papers, &lt;a href=&quot;https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html&quot;&gt;Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2023/monosemantic-features/index.html&quot;&gt;Towards Monosemanticity: Decomposing Language Models With Dictionary Learning&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2021/framework/index.html&quot;&gt;A Mathematical Framework for Transformer Circuits&lt;/a&gt;, &lt;a href=&quot;https://transformer-circuits.pub/2022/in-context-learning-and-induction-heads/index.html&quot;&gt;In-context Learning and Induction Heads&lt;/a&gt;, and &lt;a href=&quot;https://transformer-circuits.pub/2022/toy_model/index.html&quot;&gt;Toy Models of Superposition&lt;/a&gt;. This work builds on ideas from members&#39; work prior to Anthropic such as the &lt;a href=&quot;https://distill.pub/2020/circuits/&quot;&gt;original circuits thread&lt;/a&gt;, &lt;a href=&quot;https://distill.pub/2021/multimodal-neurons/&quot;&gt;Multimodal Neurons&lt;/a&gt;, &lt;a href=&quot;https://distill.pub/2019/activation-atlas/&quot;&gt;Activation Atlases&lt;/a&gt;, and &lt;a href=&quot;https://distill.pub/2018/building-blocks/&quot;&gt;Building Blocks&lt;/a&gt;.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;About the role:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;As a manager on the Interpretability team, you&#39;ll support a team of expert researchers and engineers who are trying to understand at a deep, mechanistic level, how modern large language models work internally.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;Few things can accelerate this work more than great managers. Your work as manager will be critical in making sure that our fast-growing team is able to meet its ambitious safety research goals over the coming years. In this role, you will partner closely with an individual contributor research lead to drive the team&#39;s success, translating cutting-edge research ideas into tangible goals and overseeing their execution. You will manage team execution, careers and performance, facilitate relationships within and across teams, and drive the hiring pipeline.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;If you&#39;re more interested in making individual direct technical contributions to our research as the primary focus of your role, feel free to apply to our &lt;a href=&quot;https://boards.greenhouse.io/anthropic/jobs/4020159008&quot;&gt;Research Scientist&lt;/a&gt; or &lt;a href=&quot;https://boards.greenhouse.io/anthropic/jobs/4020305008&quot;&gt;Research Engineer&lt;/a&gt; roles instead.&lt;/p&gt;
&lt;h4&gt;&amp;nbsp;&lt;/h4&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Partner with a research lead on direction, project planning and execution, hiring, and people development&lt;/li&gt;
&lt;li&gt;Set and maintain a high bar for execution speed and quality, including identifying improvements to processes that help the team operate effectively&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Coach and support team members to have more impact and develop in their careers&lt;/li&gt;
&lt;li&gt;Drive the team&#39;s recruiting efforts, including hiring planning, process improvements, and sourcing and closing&lt;/li&gt;
&lt;li&gt;Help identify and support opportunities for collaboration with other teams across Anthropic&lt;/li&gt;
&lt;li&gt;Communicate team updates and results to other teams and leadership&lt;/li&gt;
&lt;li&gt;Maintain a deep understanding of the team&#39;s technical work and its implications for AI safety&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Are an experienced manager (minimum 2-5 years) with a track record of effectively leading highly technical research and/or engineering teams&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Have a background in machine learning, AI, or a related technical field&lt;/li&gt;
&lt;li&gt;Actively enjoy people management and are experienced with coaching and mentorship, performance evaluation, career development, and hiring for technical roles&lt;/li&gt;
&lt;li&gt;Have strong project management skills, including prioritization and cross-functional coordination and collaboration&lt;/li&gt;
&lt;li&gt;Have managed technical teams through periods of ambiguity and change&lt;/li&gt;
&lt;li&gt;Are a quick learner, capable of understanding and contributing to discussions on complex technical topics and are motivated to learn about our research&lt;/li&gt;
&lt;li&gt;Are a strong communicator both in speaking and in writing&lt;/li&gt;
&lt;li&gt;Believe that advanced AI systems could have a transformative effect on the world, and are passionate about helping make sure that transformation goes well&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Experience scaling engineering infrastructure&lt;/li&gt;
&lt;li&gt;Experience working on open-ended, exploratory research agendas aimed at foundational insights&lt;/li&gt;
&lt;li&gt;Some familiarity with our work and mechanistic interpretability&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Role Specific Location Policy:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;This role is expected to be in our SF office for 3 days a week.&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$340,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$425,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Research Manager, Interpretability

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;
&lt;h2&gt;About Horizons&lt;/h2&gt;
&lt;p&gt;The Horizons team leads Anthropic&#39;s reinforcement learning research and development, playing a critical role in advancing our AI systems. We&#39;ve contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude 3.5 and 3.7 Sonnet. Our work spans several key areas:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Developing systems that enable models to use computers effectively&lt;/li&gt;
&lt;li&gt;Advancing code generation through reinforcement learning&lt;/li&gt;
&lt;li&gt;Pioneering fundamental RL research for large language models&lt;/li&gt;
&lt;li&gt;Building scalable RL infrastructure and training methodologies&lt;/li&gt;
&lt;li&gt;Enhancing model reasoning capabilities&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;We collaborate closely with Anthropic&#39;s alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and work hand-in-hand with dedicated RL engineering teams to implement our research at scale. The Horizons team sits at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.&lt;/p&gt;
&lt;/div&gt;
&lt;h2&gt;About the Role&lt;/h2&gt;
&lt;div&gt;
&lt;p&gt;As a Research Engineer on the Horizons team, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You&#39;ll work on fundamental research in reinforcement learning, creating &#39;agentic&#39; models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation.&lt;/p&gt;
&lt;/div&gt;
&lt;div&gt;
&lt;h2&gt;Representative projects:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters. Help scale our systems to handle increasingly complex research workflows.&lt;/li&gt;
&lt;li&gt;Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models.&lt;/li&gt;
&lt;li&gt;Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows.&lt;/li&gt;
&lt;li&gt;Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research.&lt;/li&gt;
&lt;/ul&gt;
&lt;/div&gt;
&lt;div&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;h2&gt;You may be a good fit if you:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Are proficient in Python and async/concurrent programming with frameworks like Trio&lt;/li&gt;
&lt;li&gt;Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX)&lt;/li&gt;
&lt;li&gt;Have industry experience in machine learning research&lt;/li&gt;
&lt;li&gt;Can balance research exploration with engineering implementation&lt;/li&gt;
&lt;li&gt;Enjoy pair programming (we love to pair!)&lt;/li&gt;
&lt;li&gt;Care about code quality, testing, and performance&lt;/li&gt;
&lt;li&gt;Have strong systems design and communication skills&lt;/li&gt;
&lt;li&gt;Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;Strong candidates may have:&lt;/h2&gt;
&lt;/div&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;ul&gt;
&lt;li&gt;Familiarity with LLM architectures and training methodologies&lt;/li&gt;
&lt;li&gt;Experience with reinforcement learning techniques and environments&lt;/li&gt;
&lt;li&gt;Experience with virtualization and sandboxed code execution environments&lt;/li&gt;
&lt;li&gt;Experience with Kubernetes&lt;/li&gt;
&lt;li&gt;Experience with distributed systems or high-performance computing&lt;/li&gt;
&lt;li&gt;Experience with Rust and/or C++&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;Strong candidates need not have:&lt;/h2&gt;
&lt;/div&gt;
&lt;div class=&quot;section page-centered&quot;&gt;
&lt;ul&gt;
&lt;li&gt;Formal certifications or education credentials&lt;/li&gt;
&lt;li&gt;Academic research experience or publication history&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Deadline to apply:&amp;nbsp;&lt;/strong&gt;None. Applications will be reviewed on a rolling basis.&amp;nbsp;&lt;/p&gt;
&lt;/div&gt;
&lt;/div&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$280,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$425,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Research Engineer, Machine Learning (Horizons) 

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;
&lt;h2&gt;About the role&lt;/h2&gt;
&lt;/div&gt;
&lt;div&gt;
&lt;p&gt;We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you&#39;ll build and scale the critical infrastructure that powers our AI safety systems. You&#39;ll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale.&lt;/p&gt;
&lt;p&gt;As part of the Safeguards team, you&#39;ll design and implement ML infrastructure that powers Claude safety. Your work will directly contribute to making AI systems more trustworthy and aligned with human values, ensuring our models operate safely as they become more capable.&lt;/p&gt;
&lt;/div&gt;
&lt;h2&gt;Responsibilities:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem&lt;/li&gt;
&lt;li&gt;Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications&lt;/li&gt;
&lt;li&gt;Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems&lt;/li&gt;
&lt;li&gt;Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards&lt;/li&gt;
&lt;li&gt;Implement automated testing, deployment, and rollback systems for ML models in production safety applications&lt;/li&gt;
&lt;li&gt;Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs&lt;/li&gt;
&lt;li&gt;Contribute to the development of internal tools and frameworks that accelerate safety research and deployment&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;You may be a good fit if you:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment&lt;/li&gt;
&lt;li&gt;Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX&lt;/li&gt;
&lt;li&gt;Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)&lt;/li&gt;
&lt;li&gt;Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads&lt;/li&gt;
&lt;li&gt;Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)&lt;/li&gt;
&lt;li&gt;Are results-oriented, with a bias towards reliability and impact in safety-critical systems&lt;/li&gt;
&lt;li&gt;Enjoy collaborating with researchers and translating cutting-edge research into production systems&lt;/li&gt;
&lt;li&gt;Care deeply about AI safety and the societal impacts of your work&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 class=&quot;text-h3_5 text-gray-700 mb2&quot;&gt;&lt;strong&gt;Strong candidates may have experience with:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul class=&quot;pt1 text-gray-700&quot;&gt;
&lt;li&gt;Working with large language models and modern transformer architectures&lt;/li&gt;
&lt;li&gt;Implementing A/B testing frameworks and experimentation infrastructure for ML systems&lt;/li&gt;
&lt;li&gt;Developing monitoring and alerting systems for ML model performance and data drift&lt;/li&gt;
&lt;li&gt;Building automated labeling systems and human-in-the-loop workflows&lt;/li&gt;
&lt;li&gt;Experience in trust &amp;amp; safety, fraud prevention, or content moderation domains&lt;/li&gt;
&lt;li&gt;Knowledge of privacy-preserving ML techniques and compliance requirements&lt;/li&gt;
&lt;li&gt;Contributing to open-source ML infrastructure projects&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Deadline to apply:&amp;nbsp;&lt;/strong&gt;None. Applications will be reviewed on a rolling basis.&amp;nbsp;&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$320,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$405,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

ML Infrastructure Engineer, Safeguards

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;&lt;strong&gt;About the role&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;As the Product Manager for the core capabilities of Claude.ai, you will shape how users harness the power of Claude in their daily work and lives across mobile platforms. You&#39;ll improve the Claude.ai experience, focusing on helping users quickly understand, adopt, and derive lasting value from its capabilities. Working at the intersection of cutting-edge AI and user experience, you&#39;ll transform Claude into an intuitive, practical tool that solves real problems for our users.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;h3&gt;&lt;strong&gt;Product Strategy &amp;amp; Vision&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Define and execute the product vision and strategy to make frontier AI capabilities accessible and valuable to a broad user base&lt;/li&gt;
&lt;li&gt;Develop and maintain a clear product roadmap that balances rapid iteration with long-term platform evolution&lt;/li&gt;
&lt;li&gt;Identify and prioritize key use cases that drive sustainable engagement and business growth&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;User Experience &amp;amp; Product Development&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Partner with design and engineering to create intuitive interfaces that help users effectively leverage Claude&#39;s capabilities&lt;/li&gt;
&lt;li&gt;Partner with research teams to productize novel model capabilities&lt;/li&gt;
&lt;li&gt;Drive rapid experimentation in prompting patterns, UI flows, and feature development to optimize user success&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Metrics &amp;amp; Impact&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Define and track core metrics for user engagement, retention, and value creation&lt;/li&gt;
&lt;li&gt;Analyze user behavior patterns to identify opportunities for product improvement and feature development&lt;/li&gt;
&lt;li&gt;Develop and validate eval frameworks for measuring AI assistance quality and user success&lt;/li&gt;
&lt;li&gt;Partner with research teams to understand how different user segments interact with and benefit from Claude&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Cross-functional Partnership&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Work closely with research teams to understand capability developments and identify productization opportunities&lt;/li&gt;
&lt;li&gt;Collaborate with sales, support, and success teams to gather insights and ensure smooth user experiences&lt;/li&gt;
&lt;li&gt;Partner with marketing to develop compelling narratives that drives adoption&lt;/li&gt;
&lt;li&gt;Engage with the security and trust teams to maintain high standards for safe and responsible AI deployment&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Qualifications:&lt;/strong&gt;&lt;/h2&gt;
&lt;h3&gt;&lt;strong&gt;Required Experience&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;6+ years of product management experience, with a track record of shipping successful consumer or prosumer applications&lt;/li&gt;
&lt;li&gt;Demonstrated ability to deeply understand user needs and translate them into clear product requirements&lt;/li&gt;
&lt;li&gt;Strong analytical skills with experience using data to drive product decisions&lt;/li&gt;
&lt;li&gt;Excellence in cross-functional collaboration and stakeholder management&lt;/li&gt;
&lt;li&gt;Clear communication skills with ability to translate complex technical concepts for various audiences&lt;/li&gt;
&lt;/ul&gt;
&lt;h3&gt;&lt;strong&gt;Preferred Qualifications&lt;/strong&gt;&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;Experience building products in the AI space&lt;/li&gt;
&lt;li&gt;Familiarity with large language models and their applications&lt;/li&gt;
&lt;li&gt;Demonstrated passion for prototyping or experimenting with new AI use cases&lt;/li&gt;
&lt;li&gt;PM experience spans both consumer and enterprise audiences&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$305,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$385,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Product Manager, Mobile

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;h2&gt;About the role&lt;/h2&gt;
&lt;p&gt;As a Data Engineer on the Economic Research team, you will build, maintain and lead the critical data engineering that powers Anthropic&#39;s research on AI&#39;s economic impact. You will work with data systems from across Anthropic, including our research tools for privacy-preserving analysis. You will work at the intersection of data engineering and software engineering.&lt;/p&gt;
&lt;p&gt;In this role, you will work closely with teams across Anthropic—including Data Science and Analytics, Data Infrastructure, Clio Engineering, Societal Impacts, and Public Policy—to build scalable and robust data systems that support high-leverage, high-impact research. Your work will enable economists and researchers—both internal and external—to understand how AI is transforming economic activity. You will have an opportunity to shape the direction of data foundations for economic research at Anthropic during a period of fast growth.&lt;/p&gt;
&lt;h2&gt;In this role, you will:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.&lt;/li&gt;
&lt;li&gt;Expand privacy-preserving tools to enable new analytic functionality to support research needs.&lt;/li&gt;
&lt;li&gt;Design and build upon novel data systems leveraging language models (e.g., CLIO) where traditional data engineering patterns don&#39;t yet exist.&lt;/li&gt;
&lt;li&gt;Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.&lt;/li&gt;
&lt;li&gt;Lead the strategic development of the economic research data foundations roadmap&lt;/li&gt;
&lt;li&gt;Ensure data reliability, integrity, and privacy compliance across all economic research pipelines and retention runs.&lt;/li&gt;
&lt;li&gt;Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.&lt;/li&gt;
&lt;li&gt;Collaborate with the broader Data Science and Analytics and Data Infrastructure teams to align on tooling, infrastructure patterns, and shared data resources.&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;You may be a good fit if you have:&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;5+ years of experience as a Data Engineer, Analytics Engineer, or Software Engineer working on data engineering or data foundations, with a track record of building and maintaining production systems&lt;/li&gt;
&lt;li&gt;Have experience with data infrastructure and large datasets in production environments.&lt;/li&gt;
&lt;li&gt;Have experience with cloud infrastructure platforms such as AWS or GCP.&lt;/li&gt;
&lt;li&gt;Design, implement and test data models for economic research.&lt;/li&gt;
&lt;li&gt;A passion for Anthropic&#39;s mission of building helpful, honest, and harmless AI and understanding its economic implications.&lt;/li&gt;
&lt;li&gt;Strong programming skills in Python and SQL, with experience building production-quality data pipelines and analytical tools.&lt;/li&gt;
&lt;li&gt;Demonstrated ability to translate ambiguous questions into concrete technical requirements and scalable solutions.&lt;/li&gt;
&lt;li&gt;A bias for action and urgency, not letting perfect be the enemy of the effective.&lt;/li&gt;
&lt;li&gt;A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.&lt;/li&gt;
&lt;li&gt;Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Deadline to apply:&amp;nbsp;&lt;/strong&gt;None. Applications will be reviewed on a rolling basis.&amp;nbsp;&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$275,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$355,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Data Engineer, Economic Research

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;
&lt;h2&gt;&lt;strong&gt;About the role:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;You want to build the cutting-edge systems that train AI models like Claude. You&#39;re excited to work at the frontier of machine learning, implementing and improving advanced techniques to create ever more capable, reliable and steerable AI. As an ML Systems Engineer on our Reinforcement Learning Engineering team, you&#39;ll be responsible for the critical algorithms and infrastructure that our researchers depend on to train models. Your work will directly enable breakthroughs in AI capabilities and safety. You&#39;ll focus obsessively on improving the performance, robustness, and usability of these systems so our research can progress as quickly as possible. You&#39;re energized by the challenge of supporting and empowering our research team in the mission to build beneficial AI systems.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models. You’ll be responsible for improving the speed, reliability, and ease-of-use of these systems.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Have 4+ years of software engineering experience&lt;/li&gt;
&lt;li&gt;Like working on systems and tools that make other people more productive&lt;/li&gt;
&lt;li&gt;Are results-oriented, with a bias towards flexibility and impact&lt;/li&gt;
&lt;li&gt;Pick up slack, even if it goes outside your job description&lt;/li&gt;
&lt;li&gt;Enjoy pair programming (we love to pair!)&lt;/li&gt;
&lt;li&gt;Want to learn more about machine learning research&lt;/li&gt;
&lt;li&gt;Care about the societal impacts of your work&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have experience with:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;High performance, large scale distributed systems&lt;/li&gt;
&lt;li&gt;Large scale LLM training&lt;/li&gt;
&lt;li&gt;Python&lt;/li&gt;
&lt;li&gt;Implementing LLM finetuning algorithms, such as RLHF&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Representative projects:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Profiling our reinforcement learning pipeline to find opportunities for improvement&lt;/li&gt;
&lt;li&gt;Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline&lt;/li&gt;
&lt;li&gt;Making changes to our finetuning systems so they work on new model architectures&lt;/li&gt;
&lt;li&gt;Building instrumentation to detect and eliminate Python GIL contention in our training code&lt;/li&gt;
&lt;li&gt;Diagnosing why training runs have started slowing down after some number of steps, and fixing it&lt;/li&gt;
&lt;li&gt;Implementing a stable, fast version of a new training algorithm proposed by a researcher&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Deadline to apply:&amp;nbsp;&lt;/strong&gt;None. Applications will be reviewed on a rolling basis.&amp;nbsp;&lt;/p&gt;
&lt;/div&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$300,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$405,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

Machine Learning Systems Engineer, RL Engineering

&lt;div class=&quot;content-intro&quot;&gt;&lt;h2&gt;&lt;strong&gt;About Anthropic&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;We are seeking a Recruiting Analytics Scientist to join our People Data Solutions team, focusing on recruiting and talent acquisition research. You&#39;ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of how we attract and assess exceptional talent. This role sits at the intersection of recruiting science, behavioral research, and talent strategy - developing novel frameworks and conducting systematic research that drives evidence-based hiring decisions across our growing organization.&lt;/p&gt;
&lt;p&gt;This role offers the opportunity to make a significant impact on both our talent acquisition practices and the broader field of recruiting science.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Responsibilities:&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Research Design &amp;amp; Scientific Inquiry&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Design and execute systematic research studies to answer fundamental questions about talent acquisition effectiveness&lt;/li&gt;
&lt;li&gt;Generate and test hypotheses about recruiting processes, candidate behavior, and hiring outcomes using rigorous experimental and quasi-experimental methods&lt;/li&gt;
&lt;li&gt;Conduct longitudinal studies tracking hiring cohorts over multiple years to understand long-term talent outcomes&lt;/li&gt;
&lt;li&gt;Perform meta-analyses of recruiting interventions across the industry to identify best practices and knowledge gaps&lt;/li&gt;
&lt;li&gt;Navigate research ethics considerations when studying candidate and employee data, ensuring responsible research practices&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Talent Analytics &amp;amp; Insights&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Transform data into actionable insights and recommendations for talent acquisition leadership&lt;/li&gt;
&lt;li&gt;Develop frameworks to measure and improve hiring quality and long-term outcomes&lt;/li&gt;
&lt;li&gt;Apply advanced analytics and experimental methods to optimize recruiting strategies&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Process Optimization &amp;amp; Operations&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Analyze and enhance end-to-end recruiting processes and team effectiveness&lt;/li&gt;
&lt;li&gt;Design research studies to identify opportunities for process improvement&lt;/li&gt;
&lt;li&gt;Support strategic initiatives including geographic expansion and competitive positioning&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Assessment &amp;amp; Decision Science&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Evaluate and improve candidate assessment methodologies&lt;/li&gt;
&lt;li&gt;Build predictive models and measurement frameworks for talent decisions&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;You may be a good fit if you:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Hold an advanced degree (Master&#39;s or PhD) in Statistics, Data Science, I/O Psychology, Economics, Behavioral Science, or related research field&lt;/li&gt;
&lt;li&gt;Have 5+ years of experience in research, people analytics, or related quantitative fields with demonstrated research methodology expertise&lt;/li&gt;
&lt;li&gt;Experience with experimental design, hypothesis testing, longitudinal research methods, and causal inference&lt;/li&gt;
&lt;li&gt;Comfortable working in the People Analytics tech stack and collaborating with data engineers&lt;/li&gt;
&lt;li&gt;Are proficient in SQL and Python/R, with experience in statistical analysis and machine learning&lt;/li&gt;
&lt;li&gt;Have experience with data visualization and can tell compelling stories with research findings&lt;/li&gt;
&lt;li&gt;Experience with causal inference, experimental design, and A/B testing&lt;/li&gt;
&lt;li&gt;Possess excellent communication skills and can influence stakeholders at all levels&lt;/li&gt;
&lt;li&gt;Thrive in ambiguity and can balance rigor with pragmatism&lt;/li&gt;
&lt;li&gt;Have a track record of challenging assumptions with data and changing long-held practices&lt;/li&gt;
&lt;li&gt;Can navigate sensitive topics diplomatically while maintaining analytical rigor&lt;/li&gt;
&lt;li&gt;Demonstrate intellectual humility and comfort with iterative discovery&lt;/li&gt;
&lt;li&gt;Use data to improve how organizations build teams&lt;/li&gt;
&lt;/ul&gt;
&lt;h2&gt;&lt;strong&gt;Strong candidates may also have:&lt;/strong&gt;&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Background in recruiting analytics specifically (not just general analytics)&lt;/li&gt;
&lt;li&gt;Experience building self-service analytics tools or dashboards&lt;/li&gt;
&lt;li&gt;Understanding of candidate lifecycle metrics and recruiting KPIs&lt;/li&gt;
&lt;li&gt;Previous experience in high-growth technology companies or AI/ML organizations&lt;/li&gt;
&lt;li&gt;Familiarity with network analysis, NLP, or advanced statistical methods&lt;/li&gt;
&lt;li&gt;Experience with BigQuery and modern data stack tools&lt;/li&gt;
&lt;li&gt;Experience with Greenhouse or similar ATS platforms&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Application Deadline:&amp;nbsp;&lt;/strong&gt;6pm PT on October 26, 2025. We encourage all interested and qualified applicants to submit their materials before this date to ensure full consideration.&lt;/p&gt;&lt;div class=&quot;content-pay-transparency&quot;&gt;&lt;div class=&quot;pay-input&quot;&gt;&lt;div class=&quot;description&quot;&gt;&lt;p&gt;The expected&amp;nbsp;base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;title&quot;&gt;Annual Salary:&lt;/div&gt;&lt;div class=&quot;pay-range&quot;&gt;&lt;span&gt;$245,000&lt;/span&gt;&lt;span class=&quot;divider&quot;&gt;&amp;mdash;&lt;/span&gt;&lt;span&gt;$300,000 USD&lt;/span&gt;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;h2&gt;&lt;strong&gt;Logistics&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;Education requirements: &lt;/strong&gt;We require at least a Bachelor&#39;s degree in a related field or equivalent experience.&lt;strong&gt;&lt;br&gt;&lt;br&gt;Location-based hybrid policy:&lt;/strong&gt; Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.&lt;/p&gt;
&lt;p&gt;&lt;strong data-stringify-type=&quot;bold&quot;&gt;Visa sponsorship:&lt;/strong&gt;&amp;nbsp;We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;We encourage you to apply even if you do not believe you meet every single qualification.&lt;/strong&gt; Not all strong candidates will meet every single qualification as listed.&amp;nbsp; Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;How we&#39;re different&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.&lt;/p&gt;
&lt;p&gt;The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp;amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.&lt;/p&gt;
&lt;h2&gt;&lt;strong&gt;Come work with us!&lt;/strong&gt;&lt;/h2&gt;
&lt;p&gt;Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. &lt;strong data-stringify-type=&quot;bold&quot;&gt;Guidance on Candidates&#39; AI Usage:&lt;/strong&gt;&amp;nbsp;Learn about&amp;nbsp;&lt;a class=&quot;c-link&quot; href=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; target=&quot;_blank&quot; data-stringify-link=&quot;https://www.anthropic.com/candidate-ai-guidance&quot; data-sk=&quot;tooltip_parent&quot;&gt;our policy&lt;/a&gt;&amp;nbsp;for using AI in our application process&lt;/p&gt;&lt;/div&gt;

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