Pay
In line with similar jobs
$166K–$207K against $166K–$240K, the middle half of what similar US postings state.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Machine Learning Research Scientist, Evaluations
Reads like a ML Engineer role: putting models into production.
San Francisco, CA; Seattle, WA; New York, NY
Live, first seen by us 69 days ago- Pay
USD 165,600–207,000/yearAnnual period assumed — pay source
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $165,600—$207,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingAnalyze model behavior to diagnose failure modes in frontier LLMs and agents
Design and build benchmarks and evaluation methods for text and multimodal models
Connect observed failures to post-training data and training fixes (SFT, RLHF, reward modeling)
Publish research findings in top-tier AI conferences
From the employer’s posting
Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents.
Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities.
Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them.
Publish research findings in top-tier AI conferences.
Education & alternatives
Ideally you’d have: - Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. - Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
About Scale AI
At Scale, our mission is to develop reliable AI systems for the world's most important decisions.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 26, 202669 days ago
- Recorded sightings
- 61
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 69
Similar jobs usually come down between day 6 and day 69.
From 4,331 similar postings that came down. Coming down is not always a hire.
Scale AI is hiring
19 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring has slowed
- Its jobs tend to stay up a long time
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities.
In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models.
You will:
- Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA.
- Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities.
- Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them.
- Publish research findings in top-tier AI conferences.
Ideally you’d have:
- Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
- Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
- Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development.
- Excellent written and verbal communication skills.
- Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals.
- Previous experience in a customer facing role.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$165,600—$207,000 USD
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $165,600—$207,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
- Location & working pattern
San Francisco, CA; Seattle, WA; New York, NY
Working pattern and location restrictions need checking in the full posting.
- Work authorization
This passage needs a closer read in the full description.