You will own the scientific foundations that enable agents and search systems to find, understand, organize, and ground their behavior in enterprise content. Develop representations, retrieval and ranking methods, context-assembly algorithms, and evaluation systems that make enterprise AI accurate, efficient, secure, and trustworthy. You will contribute new ideas and algorithms while also driving them into production systems used by millions of customers. Your work will shape the foundational capabilities that determine whether AI systems can move beyond answering questions to deeply understanding information landscapes, synthesizing knowledge, and accomplishing real-world tasks.
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
- Advance the state of the art in retrieval and context engineering, exploring approaches such as model fine-tuning, reinforcement learning, learned retrieval and context-selection policies, synthetic data, distillation, adaptive RAG, agent memory, and other emerging techniques.
- Own the end-to-end quality strategy for enterprise grounding, establishing evaluation methods and driving improvements in relevance, reasoning, factuality, citation quality, task completion, robustness, efficiency, and trustworthiness.
- Develop learning systems that improve from feedback, including user interactions, agent outcomes, human judgments, and production signals, while accounting for sparse feedback and changing enterprise content.
- Translate research into scalable product capabilities, partnering with engineering and product teams to move promising ideas from experimentation into reliable, secure, and cost-effective production systems.
- Identify and shape new research opportunities, maintaining awareness of emerging methods, developing prototypes, influencing technical architecture, and contributing publications, patents, or external research collaborations where appropriate.
- Provide scientific leadership, setting a high bar for experimental rigor, guiding technical decisions, mentoring others, and communicating findings and strategic recommendations across the organization.
Qualifications
Required Qualifications:
- Bachelor'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 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.
- Master'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 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.
- 3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
- Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
- 3+ years experience conducting research as part of a research program (in academic or industry settings).
- 1+ year(s) experience developing and deploying live production systems, as part of a product team.
- 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
- Expertise with emerging approaches such as fine-tuning, preference optimization, synthetic data generation, distillation, adaptive retrieval, or learned context-selection policies.
- Publications, patents, open-source contributions, or demonstrated thought leadership in relevant areas of machine learning or artificial intelligence.
- Familiarity with privacy, security, permissions, governance, and responsible AI considerations in enterprise environments.
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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 related field and 4+ years related experience; OR Master's +3 years; OR Doctorate +1 year; OR equivalent experience.
- Master's degree in relevant field and 6+ years related experience; OR Doctorate and 3+ years related experience; OR equivalent experience.
- 3+ years creating publications (patents, libraries, peer-reviewed academic papers).
- Experience presenting at conferences or industry events as an invited speaker.
- 3+ years conducting research as part of a research program (academic or industry).
- 1+ year developing and deploying live production systems as part of a product team.
- 1+ year developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
- Expertise with approaches such as fine-tuning, preference optimization, synthetic data generation, distillation, adaptive retrieval, or learned context-selection policies.
- Publications, patents, open-source contributions, or demonstrated thought leadership in machine learning or AI.
- Familiarity with privacy, security, permissions, governance, and responsible AI considerations in enterprise environments.
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
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.
