Pay
In line with similar jobs
$128K–$267K against $166K–$240K, the middle half of what similar US postings state.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
United States of America
Open 3 months, first seen by us 106 days agoWe believe that a diverse and inclusive workplace strengthens Yahoo and deepens our relationships. When you support everyone to be their best selves, they spark discovery, innovation and creativity. Among other efforts, our 11 employee resource groups (ERGs) enhance a culture of belonging with programs, events and fellowship that help educate, support and create a workplace where all feel welcome. The compensation for this position ranges from $128,250.00 - $266,875.00/yr and will vary depending on factors such as your location, skills and experience.The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more. Currently work for Yahoo? Please apply on our internal career site.Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Design, build, and deploy real-time personalization ML capabilities
Build production LLM-backed applications and agentic workflows
Deploy and optimize ML/LLM models for real-time production serving
Process petabyte-scale data streams to derive insights from mail data
Build automated feedback loops and fallback paths for model failures
Design, build, and deploy high-throughput AI/ML capabilities that power real-time personalization
Spearhead the implementation and orchestration of production LLM-backed applications and agentic workflows
Deploy and optimize ML/LLM models for real-time production serving
Process petabyte-scale data streams using big data processing and ML techniques
Implement automated feedback loops and graceful recovery paths to handle model failure modes
Experience: 5+ years of professional experience engineering and deploying production machine learning or data science systems at scale.
Communication: Excellent verbal and written communication skills for effective collaboration with cross-functional and global engineering teams.
Qualifications - Education: Bachelor’s degree in Computer Science, Data Science, AI, or a related field; or, equivalent experience. - Experience: 5+ years of professional experience engineering and deploying production machine learning or data science systems at scale.
- Experience: 5+ years of professional experience engineering and deploying production machine learning or data science systems at scale. - Technical Proficiency: Proficient in Python or Java, with deep hands-on expertise in standard ML frameworks (PyTorch, TensorFlow, Hugging Face, Scikit-learn). - Generative & Agentic AI: Demonstrated experience building LLM-based applications or agentic systems (multi-step reasoning, tool usage, RAG, or autonomous workflows).
Preferred Qualifications - Cloud Infrastructure: Direct experience building and scaling ML pipelines on Google Cloud Platform (GCP) or similar native public cloud environments. - Domain Expertise: Prior experience working with email systems, large-scale consumer web platforms, NLP, or search architecture.
- High-Performance Inference: Experience deploying and serving models in production using tools like vLLM, TensorRT-LLM, Triton Inference Server, or ONNX Runtime. - Big Data Handling: Hands-on experience processing large datasets using Spark, Hadoop, or cloud-native data pipelines. - Communication: Excellent verbal and written communication skills for effective collaboration with cross-functional and global engineering teams.
Open 3 monthsWe first saw this posting 106 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
In line with similar jobs
$128K–$267K against $166K–$240K, the middle half of what similar US postings state.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Day 106
Up longer than most. Similar jobs usually come down between day 8 and day 76.
At Yahoo, jobs usually come down by about day 121.
From 5,460 similar postings that came down, and 8 of Yahoo’s. Coming down is not always a hire.
4 open jobs
Check the employer’s posting for the current role and application details.
Already applied? Track this application
Yes. We’ve followed one other Senior Machine Learning Engineer job there since July 2026. It is still up.
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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.
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.
A Little About Us
Yahoo Mail is the ultimate Consumer Inbox with over 220 million monthly active users. We empower users to run the business of their lives through a fast, intuitive platform while managing billions of daily inbound connections and petabytes of efficient storage. Our engineering team is actively transitioning to a 100% native public cloud architecture.
The Mail Intelligence Org develops intelligent capabilities at scale to uncover user interests, reveal habits, and personalize user journeys across Yahoo Mail and the broader Yahoo ecosystem. We manage billions of messages using advanced backend systems and state-of-the-art AI - including NLP, Generative AI, and autonomous agentic workflows. We are a team of passionate engineers dedicated to high coding standards, world-class architecture, and an owner’s mindset.
A Lot About You
AI-First Mindset: AI is core to how you work, innovate, and deliver results. You actively experiment with advanced tools (e.g., Claude, Cursor, Codex), integrate them into your daily development workflows, and measure success by how effectively you leverage AI to solve complex problems.
Agentic Thinker: You have hands-on experience designing, orchestrating, and evaluating agentic systems (multi-step reasoning, tool integration, memory, autonomous workflows, and LLM-based agents) in production environments.
Engineering Standards: You take extreme ownership of your work, bringing high engineering rigor, clean code practices, and a focus on building scalable, fault-tolerant architectures.
Collaborative Partner: You thrive in cross-functional, global engineering environments, working closely with Tech Leads, Architects, and Engineers to deliver robust features.
Continuous Learner: You stay on the cutting edge of rapid advancements in machine learning, generative models, and infrastructure trends, continuously bringing novel approaches into practice.
Responsibilities
Architect & Personalize: Design, build, and deploy high-throughput AI/ML capabilities that power real-time personalization and deep insights for hundreds of millions of users.
GenAI & Agentic Systems: Spearhead the implementation and orchestration of production LLM-backed applications and agentic workflows (prompt engineering, tool integration, and automated feedback loops).
AI-Driven Execution: Embed AI-first practices into daily development cycles using AI-assisted tools to accelerate iteration, improve code quality, and modernize engineering workflows.
Data-Driven Intelligence: Process petabyte-scale data streams using big data processing and ML techniques to derive key insights from mail metadata and content.
Inference at Scale: Deploy and optimize ML/LLM models for real-time production serving using modern frameworks (e.g., vLLM, TensorRT-LLM, Triton, ONNX Runtime).
Resilience & Fallback Design: Implement automated feedback loops and graceful recovery paths to handle model failure modes smoothly, maintaining high service availability and user satisfaction.
Tradeoff Management: Balance compute costs, latency, quality, and model performance to optimize systems for massive consumer scale.
Qualifications
Education: Bachelor’s degree in Computer Science, Data Science, AI, or a related field; or, equivalent experience.
Experience: 5+ years of professional experience engineering and deploying production machine learning or data science systems at scale.
Technical Proficiency: Proficient in Python or Java, with deep hands-on expertise in standard ML frameworks (PyTorch, TensorFlow, Hugging Face, Scikit-learn).
Generative & Agentic AI: Demonstrated experience building LLM-based applications or agentic systems (multi-step reasoning, tool usage, RAG, or autonomous workflows).
High-Performance Inference: Experience deploying and serving models in production using tools like vLLM, TensorRT-LLM, Triton Inference Server, or ONNX Runtime.
Big Data Handling: Hands-on experience processing large datasets using Spark, Hadoop, or cloud-native data pipelines.
Communication: Excellent verbal and written communication skills for effective collaboration with cross-functional and global engineering teams.
Preferred Qualifications
Cloud Infrastructure: Direct experience building and scaling ML pipelines on Google Cloud Platform (GCP) or similar native public cloud environments.
Domain Expertise: Prior experience working with email systems, large-scale consumer web platforms, NLP, or search architecture.
AI Tooling: Early adoption and proactive integration of modern developer tooling (Cursor, Claude, Codex) directly into daily development practices.
The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies; exercising sound judgment; working effectively, safely and inclusively with others; exhibiting trustworthiness and meeting expectations; and safeguarding business operations and brand integrity.
At Yahoo, we offer flexible hybrid work options that our employees love! While most roles don’t require regular office attendance, you may occasionally be asked to attend in-person events or team sessions. You’ll always get notice to make arrangements. Your recruiter will let you know if a specific job requires regular attendance at a Yahoo office or facility. If you have any questions about how this applies to the role, just ask the recruiter!
Yahoo is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. Yahoo will consider for employment qualified applicants with criminal histories in a manner consistent with applicable law. Yahoo is dedicated to providing an accessible environment for all candidates during the application process and for employees during their employment. If you need accessibility assistance and/or a reasonable accommodation due to a disability, please submit a request via the Accommodation Request Form (www.yahooinc.com/careers/contact-us.html) or call +1.866.772.3182. Requests and calls received for non-disability related issues, such as following up on an application, will not receive a response.
We believe that a diverse and inclusive workplace strengthens Yahoo and deepens our relationships. When you support everyone to be their best selves, they spark discovery, innovation and creativity. Among other efforts, our 11 employee resource groups (ERGs) enhance a culture of belonging with programs, events and fellowship that help educate, support and create a workplace where all feel welcome.
The compensation for this position ranges from $128,250.00 - $266,875.00/yr and will vary depending on factors such as your location, skills and experience.The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more.Currently work for Yahoo? Please apply on our internal career site.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
We believe that a diverse and inclusive workplace strengthens Yahoo and deepens our relationships. When you support everyone to be their best selves, they spark discovery, innovation and creativity. Among other efforts, our 11 employee resource groups (ERGs) enhance a culture of belonging with programs, events and fellowship that help educate, support and create a workplace where all feel welcome. The compensation for this position ranges from $128,250.00 - $266,875.00/yr and will vary depending on factors such as your location, skills and experience.The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more. Currently work for Yahoo? Please apply on our internal career site.
United States of America
This passage needs a closer read in the full description.
No clear work-authorization passage found. Eligibility is unconfirmed.
We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting