AI assistants are only as good as the information behind their answers. Our team builds the search and grounding technology that finds the right information for each request, across email, documents, meetings, chats and people, and connects AI-generated answers to the sources that support them. This work sits on the critical path: getting it right improves relevance, limits hallucinations and earns user trust.
We work across the full retrieval stack: understanding what a person is really asking, turning everyday, messy requests into precise queries, blending lexical and semantic retrieval, and deciding when enough evidence has been found. Modern language models run throughout, and we fine-tune them with supervised and reinforcement learning so they find better evidence with less wasted effort. Improvements are measured offline on relevance, accuracy, citation quality and speed, then confirmed in online experiments before they ship.
We are looking for a Senior Applied Scientist to help drive this work. You will take on hard, open-ended problems in search and grounding and own them end to end, from framing the problem and building the data through modeling, evaluation and deployment, while helping set the scientific direction for the team. Much of the work happens in a privacy-first environment where models are trained and evaluated without direct access to customer data, so creativity with synthetic data and evaluation design is essential.
The impact is broad: our work improves search in Outlook, Teams, SharePoint and OneDrive and grounds the answers in Microsoft 365 Copilot, reaching tens of millions of people at work. The role spans science and engineering, so you can learn everything from writing production code to training the latest language models, and everything in between. People who thrive here love turning ambiguity into robust systems, balance machine learning and information retrieval fundamentals with production pragmatism, and care about user trust, performance and clarity of outcomes.
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 how AI systems search for information: understanding what a person needs, turning requests into precise queries, choosing where to look, and recognizing when enough evidence has been found.
Improve the quality, coverage and reliability of grounding data, so answers are relevant, accurate and supported by the sources they cite.
Train and fine-tune language models for search and grounding tasks, using supervised fine-tuning and reinforcement learning to improve both quality and speed.
Design evaluation methods and reward signals that reflect what users value, such as relevance, accuracy, trustworthy citations and efficiency.
Build training and evaluation data in privacy-preserving ways, including synthetic data generation.
Define offline and online metrics for search and answer quality, and make sure offline gains predict what people experience in production.
Dig into real-world failures, find root causes and turn them into model, data and system fixes that ship.
Partner with engineering, product, ranking and research teams to take new techniques from experiment to production, across many languages and markets.
Mentor scientists and engineers, raise the bar on experimental rigor, and communicate results and trade-offs clearly to technical and non-technical audiences.
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.
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:
- Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field AND 6+ years related experience
- OR Doctorate in one of these fields AND 3+ years related experience
- OR equivalent experience.
- Solid foundation in information retrieval and search, including query understanding, retrieval, ranking and relevance evaluation.
- Experience building retrieval-augmented generation (RAG), agentic search or other systems that ground language model outputs in external data.
- Hands-on experience training or fine-tuning language models, such as supervised fine-tuning or reinforcement learning, and shipping the results to production.
- Experience designing evaluation metrics, test sets or model-based judges for search or answer quality.
- Solid experimentation skills, including statistical significance testing, A/B experiments and turning results into product decisions.
- Experience working with sensitive data under privacy constraints, including synthetic data generation.
- Proficiency in Python and modern machine learning frameworks such as PyTorch, and experience working with large-scale data.
- A track record of publications, patents or equivalent applied impact, and the ability to explain complex results to technical and non-technical audiences.
#CAP #Copilot
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.
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