As a Principal Applied Scientist, you’ll be responsible for delivering mission-critical innovations that directly improve Copilot experiences. Your team will work on: Adapting advanced vector search algorithms (e.g., FAISS, ANN, ScaNN) for enterprise-scale semantic retrieval and Improving classic and neural keyword search quality through deep language understanding. Designing and training relevance models, including LLM fine-tuning and learning-to-rank (LTR) approaches. Building robust evaluation pipelines using offline metrics and online A/B experimentation. Driving cross-org collaboration with platform partners, other applied science teams, and product teams across time zones
This is a highly impactful role requiring a mix of technical depth, strategic execution to shape the next generation of AI-powered search experiences.
We foster a culture driven by growth mindset, collaboration, and inclusive innovation, rooted in our core values of respect, integrity, and accountability.
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
- Drive end-to-end applied science projects: From ideation and design to implementation, experimentation, and shipping, you will lead high-impact projects that directly improve Copilot Chat, Copilot Search, and BizChat experiences. This includes identifying search and relevance gaps, formulating innovative hypotheses, and delivering scalable solutions.
- Innovate with scientific rigor: Invent and apply cutting-edge techniques in machine learning, natural language processing, and information retrieval to address real-world challenges at enterprise scale. You will design novel approaches for improving retrieval, ranking, query understanding, and semantic search in Copilot systems.
- Document, share, and amplify learnings: Promote a culture of transparency and innovation by capturing experimental results, documenting methodology, and publishing internal learnings. You’ll drive knowledge sharing that enables broader impact across the organization.
- Translate business goals into scientific strategy: Partner closely with product and business stakeholders to align team efforts with high-priority objectives. You will translate ambiguous product requirements into clear, data-driven, and technically feasible directions.
- Collaborate across organizations and time zones: Work cross-functionally with platform engineering teams, peer science orgs, and product managers to ensure alignment, resolve dependencies, and unblock progress. You’ll be a key bridge between applied science innovation and product delivery.
Qualifications
Required Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 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 5+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
Preferred Qualifications:
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 8+ years of industrial programming experience in modern languages such as Python, Java, C++, or C#, including production-level ML pipelines.
- Demonstrated expertise in data analysis at scale, including working with logs, telemetry, and large datasets to uncover behavioral patterns, build evaluation datasets, and derive insights.
- Familiarity with modern machine learning and deep learning frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers.
- Proven ability to collaborate across engineering, product, and science organizations and to communicate technical details clearly to both technical and non-technical stakeholders.
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.
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