Principal Applied Science Manager

Microsoft is on a mission to reinvent productivity with AI, and the Copilot for Calendar initiative is at the forefront of this effort. We are seeking a Principal Applied Science Manager to lead the development of AI-powered calendar experiences that help users organize and manage time more effectively. In this role, you will:

• Keep abreast of the latest breakthroughs in generative AI and large-language models and translate them into practical, high-impact calendar Copilot solutions that leverage M365 graph to deliver personalized, context-aware solutions for time management.
• Define and iterate on relevance metrics that measure how Copilot features truly serve user intent in M365 Calendar.
• Determine where fine-tuned LLMs (large language models), small language models, or other specialized approaches are required—and own their design, training, and deployment.
• Build high-fidelity synthetic and manufactured datasets, along with rigorous evaluation sets and benchmarks that mirror the workflows of enterprise information-workers.
• Drive the applied-science strategy for industry-leading calendar agents, partnering closely with engineering and product teams to ship at scale.
• Build a clear, inspiring vision that aligns every team member around ambitious, measurable goals.
• Recruit and nurture diverse talent, fostering a culture of ownership, psychological safety, and relentless learning.
• Empower the team with resources and trust, then remove obstacles so they can execute rapidly and deliver outsized, sustainable impact.

You will drive innovation in Copilot solutions for the calendar ecosystem and build intelligent AI forward calendar features (e.g. smart scheduling and conflict resolution, meeting prep, protecting and reclaiming your time, planning your day / week etc.). If you thrive at the intersection of cutting-edge AI research, real-world product impact across 100s of millions of users and love building a hard-working team that chases impact while having fun along the way, we’d love to meet you.

 

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

• Innovation with LLMs: Stay at the cutting edge of NLP (natural language processing) and large language models. Apply techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) to enhance Copilot’s capabilities. You will explore new model architectures and external knowledge integration to push the boundaries of what Copilot can do in the calendar domain.
• Lead AI Feature Development: Lead the design and development of advanced ML/NLP models to power Copilot features in Outlook Calendar and Microsoft Teams. Leverage large language models and diverse data (emails, meetings, documents, chat transcripts etc) to create intelligent solutions for time management.
• Modeling & Personalization: Architect and refine machine learning models (supervised and unsupervised) that optimize the relevance and personalization of calendar features.
• Experimentation & Evaluation: Continuously iterate on models using real user feedback and telemetry, ensuring each new version of the Copilot delivers higher precision, recall and better user satisfaction.
• Product Integration: Work closely with engineering and product teams to integrate your AI models into Calendar. Ensure solutions are production-ready – meeting standards for scalability, security, compliance, and real-time performance in a cloud environment. You will translate broad product needs into robust AI services that operate reliably at Microsoft scale (millions of users).
• Technical Leadership & Mentorship: Provide technical leadership within the team and across partner groups. Mentor applied scientists and machine learning engineers, fostering best practices in research, experimentation, and coding. Guide technical initiatives and ensure scientific rigor in how the team builds and evaluates AI solutions. Champion a culture of collaboration, learning, and rapid innovation to continuously improve our AI-powered productivity features.
• Team Building: Set a bold, customer-centric mission that galvanizes the team and clarifies priorities. Assemble complementary skill sets, cultivate candid collaboration, celebrate innovation, clear roadblocks, amplify wins, and hold a high bar for accountability—turning collective momentum into outsized, repeatable results.
• Provide expertise in building and scaling relevance and ranking systems, including experience with retrieval, embeddings, and evaluation methodologies tailored to LLM-powered applications.
• Demonstrate leadership in developing AI/ML solutions for productivity or assistant-like experiences, with a strong track record of managing cross-functional collaborations and driving measurable impact through data-driven product iteration.

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.
• 3+ years of people management experience.
• 4+ years experience in experimentation and evaluation using user feedback and telemetry to improve performance.
• Deep experience with large language models (LLMs), including techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).

Other Requirements: 

Candidates must be able to meet Microsoft, customer and/or government security screening requirements that 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 related field AND 12+ 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.
• 7+ years of people management experience.
• Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• 7+ years experience conducting research as part of a research program (in academic or industry settings).
• 5+ years experience developing and deploying live production systems, as part of a product team.
• 7+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
• Deep understanding of modern machine learning techniques, including natural language processing and deep learning. Demonstrated experience working with large language models (LLMs) and advanced NLP algorithms to solve real-world problems.
• 8+ years of hands-on experience developing and deploying machine learning or AI solutions in a production environment (industry or research lab). Proven track record of taking ML projects through the full life cycle – from initial concept and prototyping to shipping at scale.
  
• Strong coding skills in languages such as Python (and/or C++/Java) and proficiency with machine learning frameworks and tools (e.g. PyTorch or TensorFlow).
  
• Strong analytical skills in handling large-scale data and evaluating model performance. Familiarity with defining and tracking ML metrics (precision/recall, etc.) and using feedback to improve models. Ability to rigorously analyze experiment results and troubleshoot model behavior in an iterative development process.

Applied Sciences M6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 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 $220,800 - $331,200 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

Microsoft will accept applications for the role until July 4, 2025.

 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

 

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

 

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