Senior Applied Scientist

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Applied Sciences

Senior Applied Scientist role focused on designing and developing LLMs and agentic systems for Microsoft 365 Copilot. The role bridges research and engineering, building core agent capabilities, and scaling AI features into production. Responsibilities include applying scientific rigor, evaluating models, and collaborating across teams to deliver impactful AI solutions.

What you'd actually do

  1. Build deep expertise in applied research and modern LLM and ML techniques, and apply it to influence product needs and scientific direction.
  2. Review business and product requirements, incorporate research, and apply scientific rigor to design, develop, and evaluate methods and models that deliver measurable impact.
  3. Collaborate with stakeholders to understand user requirements, gather feedback, and iteratively improve models and solutions.
  4. Design, implement, and deploy AI/ML solutions that meet quality, scalability, and reliability standards, and translate project vision into actionable milestones, estimates, and plans.
  5. Document experiments and share findings to promote innovation, and contribute to ethics and privacy practices related to research and data collection.

Skills

Required

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience
  • equivalent experience

Nice to have

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • equivalent experience
  • 1+ years experience designing, developing, and evaluating ML models, LLM-based systems, or data-intensive research and evaluation systems.
  • Demonstrated ability to ramp up quickly, work independently, and make measurable impact in fast-paced and ambiguous environments
  • Collaboration skills and ability to work effectively across multiple teams and disciplines to deliver complex projects.
  • 2+ years experience developing and deploying AI/ML or GenAI products or systems at multiple points in the product cycle from ideation to shipping.
  • Experience developing, fine-tuning, or evaluating large language models (LLMs) and GenAI systems.
  • Experience conducting research as part of a research program (in academic or industry settings), including publications such as patents, libraries, or peer-reviewed academic papers.
  • A growth mindset, passion for continuous learning, and drive to make both systems and teams more efficient and effective.

What the JD emphasized

  • design and develop LLMs (Large Language Models) and underlying subsystems
  • build and evaluate models
  • develop custom LLM architectures and methods for specific product needs
  • translate research into high-quality production systems
  • design, implement, and deploy AI/ML solutions
  • developing and deploying AI/ML or GenAI products or systems at multiple points in the product cycle from ideation to shipping
  • developing, fine-tuning, or evaluating large language models (LLMs) and GenAI systems

Other signals

  • building core agent capabilities
  • incubating emerging technologies
  • partner with engineers, researchers, and product teams to prototype bold ideas
  • validate them in real-world scenarios
  • transition them into production-ready systems
  • design and develop LLMs (Large Language Models) and underlying subsystems tailored to various product scenarios and GenAI capabilities
  • apply scientific rigor to problems that empower teams across the organization
  • deliver best-in-class solutions
  • build and evaluate models
  • develop custom LLM architectures and methods for specific product needs
  • translate research into high-quality production systems