Responsibilities
Efficient hosting of large language models and parameter-efficient adapters
Architectural or parameter‑efficient adaptation techniques
Inference‑time steering or controllability approaches
Tooling for evaluation, debugging, or model development
Harnesses
Implement and evaluate adaptation approaches under real‑world enterprise deployment constraints such as latency, safety, privacy, policy compliance, and compute efficiency.
Partner with research and engineering teams to translate product or customer requirements into scalable model adaptation solutions.
Drive technical work from concept to prototype, delivering new methods, systems components, or empirical insights that advance enterprise model customization.
Document approaches and share best practices to improve organizational capabilities in post‑training and secure deployment of foundation models.
Qualifications
Required Qualifications
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience.
Other Requirements
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
Experience contributing to open-source systems, or production deployments involving foundation model training or adaptation.
Experience in one or more of the following areas
Reinforcement learning or post-training methods
Distributed or large‑scale ML training systems
Evaluation or benchmarking of AI systems
Tool use, planning, or agentic model behaviors
Deployment of AI solutions in enterprise or customer environments
1+ years of experience building scalable ML systems or pipelines for training, adapting, or deploying AI models.
2+ years of experience with Python and machine learning frameworks (e.g., PyTorch or equivalent)
#M365
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800 - $219,200 per year.
- Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
- https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
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.
