The Microsoft 365 Copilot Reasoning Science team is looking for a Principal Applied Scientist to help shape the future of enterprise productivity by building reliable, long-horizon agentic capabilities for M365 Copilot Chat. In this role, you’ll advance the state of the art in frontier-model harness engineering and evaluation, tackling the challenges required for AI agents to reliably plan, reason, and execute complex, multi-step tasks on behalf of millions of users.
The ideal candidate is a self-starter who thrives in a fast-paced, high-visibility environment, and is passionate about being data-driven, iteration speed, scale, and engineering culture. You will be presented with opportunities to have great impact, work with frontier models, and collaborate closely with teams across the company, including Microsoft Research, Azure, and MAI.
The team is part of CACore (Copilot and Agents Core Platform), an organization that brings together talent in the areas of LLMs (Large Language Models), recommender systems, machine learning, information retrieval, agentic engineering, and responsible AI. This role is flexible in that you will be able to partner with your manager to define the way that you’d like to work, whether in the office or from home.
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.
Responsibilities
Defining and managing experiments from inception to shipment, creating the requisite metrics, ML pipelines, algorithms. Owning problems end-to-end and being willing to pick up whatever knowledge you’re missing to get the job done.
Defining rigorous evaluation methodologies, offline benchmarks, online experimentation frameworks and data-driven approaches for measuring model and product performance.
Influencing senior leadership and partner teams through quality written and oral summaries of work in progress and experimentation results.
Building tools to accelerate your own (and your teammates’) workflows, but only when off-the-shelf solutions won’t do.
Contributing to strategic planning and long-term technical roadmaps, incorporating latest research to meet business goals.
Contributing to the growth and development of the team’s engineers and applied scientists. Identifying new research talent to join Microsoft and collaborating with the academic community to develop the recruiting pipeline.
Supporting and developing a thriving applied science culture within CASQ to encourage experimentation, scientific process, and innovation.
Qualifications
Required Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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 4+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
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:
- Proficiency in agentic engineering.
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- 5+ year(s) building and maintaining production machine learning systems at internet scale.
- 3+ year(s) experience in working with multidisciplinary, geo-distributed team.
- Demonstrated experience owning end-to-end machine learning and software projects, including gathering requirements and feedback, collaborating with cross-functional stakeholders, producing technical designs, shipping to production, and iterating on systems post-launch.
- Ability to thrive in dynamic environments, especially where priorities may shift and project definitions evolve.
- Advanced expertise in agentic engineering.
Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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.
Skills Required
- Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 6+ years of related experience; or equivalent experience
- Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 4+ years of related experience; or equivalent experience
- Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 3+ years of related experience; or equivalent experience
- Pass the Microsoft Cloud background check upon hire or transfer and every two years thereafter
- Proficiency in agentic engineering
- Master's degree in a relevant field plus 9+ years of related experience, or doctorate plus 6+ years, or equivalent experience
- 5+ years creating publications, such as patents, libraries, or peer-reviewed academic papers
- 5+ years building and maintaining production machine learning systems at internet scale
- 3+ years working with multidisciplinary, geographically distributed teams
- Experience owning end-to-end machine learning and software projects, including requirements gathering, technical design, production delivery, and post-launch iteration
- Ability to thrive in dynamic environments with shifting priorities and evolving project definitions
- Advanced expertise in agentic engineering
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
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Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
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Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
Microsoft Insights
What We Do
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