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About the Role
We are seeking a Senior Machine Learning Engineer - Applied Scientist to define, evaluate, and build next-generation AI-powered product experiences. This role requires a leader with deep applied science expertise in LLMs, evaluation systems, AI, MLOps, experimentation, and software engineering, combined with strong product judgment and a proven ability to ship high-quality AI solutions. You will shape how AI capabilities are developed, measured, improved, and brought into production.
Responsibilities
- Lead applied science strategy for AI-powered product areas, from opportunity identification through experimentation, launch, and continuous improvement.
- Define success metrics for AI product experiences, including customer value, quality thresholds, reliability, safety, engagement, and business impact.
- Design and operationalize LLM evaluation frameworks across the product development lifecycle.
- Build evaluation methodologies for LLM-based, agentic, retrieval-augmented, and multimodal AI systems.
- Develop offline experimentation and evaluation pipelines to compare models, prompts, system designs, and product behavior.
- Partner with engineering and PM leadership to align science priorities with product strategy and execution.
- Work with software engineering teams to produce AI systems with strong attention to reliability, scalability, latency, observability, maintainability, and MLOps best practices.
- Drive iteration cycles by forming hypotheses, defining metrics, running experiments, interpreting results, and recommending actions.
- Establish quality bars and decision-making frameworks for AI launches.
- Mentor scientists and engineers, raise the technical bar, and influence cross-team best practices for AI development, experimentation, and evaluation.
- Communicate findings, tradeoffs, risks, and recommendations clearly to stakeholders.
Requirements
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience OR equivalent experience.
- Ability to meet Microsoft, customer and/or government security screening requirements.
- Must pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Skills
- LLMs
- Evaluation systems
- AI
- MLOps
- Experimentation
- Software engineering
- Product judgment
- Prompt engineering
- RAG
- Agents
- Tool use
- Model comparison
- Failure analysis
- Dataset creation
- Annotation strategies
- Automated and human evaluation
- Benchmark design
- Regression testing
- Launch criteria
- Production monitoring
- Offline experiments
- Multimodal AI systems
- Product success metrics
- Customer/business goals
- Scientific and technical objectives
- Reliability
- Scalability
- Latency
- Observability
- Maintainability
- Responsible AI
Location
- U.S.
Work Type
- Full-time
Experience Level
- Senior
- Applied Scientist
Education Level
- Bachelor's Degree
- Master's Degree
- Doctorate
Salary/Compensations
- USD $119,800 - $234,700 per year (U.S. typical base pay range)
- USD $160,200 - $261,000 per year (San Francisco Bay area and New York City metropolitan area)
Benefits
- Certain roles may be eligible for benefits and other compensation.
About the Company
- Microsoft’s mission is to empower every person and every organization on the planet to achieve more.
- As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.
- Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Equal Opportunity
- Microsoft is an equal opportunity employer.
- All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.
- If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.