Principal Applied Scientist

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This person will collaborate with a multi-functional group to deliver next generation innovations and experiences leveraging, fine tuning and prompt engineering foundation models. Partner with product and engineering teams to invent and deliver on the future for Microsoft CoPilot and other generative AI products. If yes, you'll love this opportunity.

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.

Required Qualifications:

• Bachelor'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 Master'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 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.
• 4+ years of experience in software development, preferred hands on experience on developing AI Applications
  
• Experience in applied science experiments, create and validate metrics, work with ML pipeline and modeling algorithm in the area of Large Language Models, Natural Language Processing, Information Retrieval, and Machine Learning.
  

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 related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
• 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
• 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
• Develop and deploy conversational and language understanding models at scale.
  
• Following and advancing best practices for Responsible AI and Privacy Preserving Machine Learning.
  
• Collaborate closely with Microsoft Research, Microsoft AI groups, Microsoft Azure, AI platform teams, and product teams to create the next generation of AI innovation in our products and services.
  
• Experience with commercial product development with a focus on user experiences.

Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $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

Microsoft will accept applications for the role until August 8, 2025.

• Design, implement, validate, and ship AI-powered features end-to-end for Microsoft Teams across desktop, web, and mobile clients.
• Collaborate with Program Managers, Designers, and Researchers to define product requirements, timelines, and measurable success criteria.
• Maintain and improve system performance, reliability, latency, and scalability of AI-powered features in production.
• Participate in code reviews, debugging, telemetry reviews, and continuous delivery processes.
• Champion a culture of scientific rigor, ethical AI, and innovation across the team.
• Communicate scientific findings and technical designs clearly to product and engineering leadership.
• Drive exploration of hybrid AI experiences (cloud + edge + LLM) for responsiveness, privacy, and enterprise value.
• Experience prompt tuning, fine tuning and RAG system development, experience with Evaluation, A/B testing, Experimentation.