The Time and Places team at Microsoft is at the forefront of redefining how people organize, schedule, and collaborate through intelligent calendar and meeting experiences. We build AI-powered solutions that enhance productivity-from personalized briefings and intelligent time suggestions to enhance time management experience. Our work spans deep data science, large language model (LLM) integration, and telemetry-driven insights to deliver seamless, @context-aware user experiences across Microsoft 365. We partner closely with product, engineering, and research teams to drive innovation that scale globally and impacts millions of users daily.
Microsoft Copilot is revolutionizing how people work and has created an unprecedented opportunity to advance the state-of-the-art in a way that benefits millions of people. As an Applied Scientist , your core mission will be to deliver exciting innovation in Microsoft Copilot. We are looking for candidates who are creative, self-driven, curious, people-oriented and comfortable defining a path through ambiguity towards high-level goals. The successful applicant(s) will collaborate closely with people across Microsoft's product teams and Microsoft Research to see their ideas realized in products and services that are used worldwide, as well as to contribute back to the scientific community and beyond (e.g. via presentations, publications, media interviews, and similar).
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
Lead applied research projects that advance the state-of-the-art in GenAI and directly impact Microsoft's core productivity products.
Collaborate closely with product, engineering, and design teams to translate research breakthroughs into practical, high-value applications.
Serve as a bridge between research and product, effectively communicating complex concepts and project progress to ensure stakeholder alignment.
Mentor colleagues and champion research best practices, sharing your expertise in state-of-the-art machine learning techniques.
Work iteratively in a research environment, developing new hypotheses and demonstrating the ability to learn from unexpected or ambiguous outcomes.
Share research findings through publications, presentations, and internal forums to influence both the scientific community and internal product strategy.
Effectively communicate with product leaders (and often MSR researchers) throughout the planning and execution of applied research projects, which often involves learning and teaching complex concepts.
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.
Experience developing and deploying large language models (LLMs), including agentic systems, supervised fine-tuning, and Reinforcement Learning (RLHF)
Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) pipelines and advanced @context engineering.
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.
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
Hands-on experience with modern LLM evaluation techniques, including LLM-as-a-Judge, agentic evaluations, and RAG assessments.
Experience delivering successful, large-scale applied ML projects in an industry setting.
Deep understanding of fundamental ML algorithms (supervised, unsupervised) and modern neural network architectures.
Experience with MLOps practices, including model versioning, automated testing, monitoring, and CI/CD for machine learning.
A record of publication in top-tier scientific venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, KDD).
Ability to translate complex ML concepts into business value and communicate technical insights to non-technical stakeholders.
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 per year.
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 $158,400 - $258,000 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
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
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Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .
