Applied Scientist II

Microsoft Microsoft · Big Tech · United States · Applied Sciences

Applied Scientist II role at Microsoft focusing on integrating AI research into productivity products like M365 Copilot. The role involves defining and leading research projects, collaborating with cross-functional teams, and contributing to the scientific community through publications. Research areas include reinforcement learning, agentic systems, multimodal modeling, post-training techniques, and LLM applications.

What you'd actually do

  1. Defining, leading, and helping to conduct research projects that simultaneously advance the state-of-the-art and directly benefit Microsoft’s core productivity products.
  2. Shape product direction by integrating rigorous scientific methods into the product lifecycle.
  3. Collaborating and coordinating with people in a range of roles, including researchers, engineers, product managers, designers, and other key product stakeholders. Serving as a bridge between research and product.
  4. Teaching, guiding, and tutoring colleagues without research backgrounds in state-of-the-art techniques and research best practices.
  5. Sharing your research with others via a range of means, including publication, to enable others to build on your work and to contribute to the understanding of our products as cutting-edge and science driven.

Skills

Required

  • 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.

Nice to have

  • At least one internship or prior role at a leading technology company, or start-up, or related organizations.
  • A record of publications in top-tier scientific venues (e.g., NeurIPS, ICML, ICLR, ACL, NAACL, KDD, WWW, CHI, PNAS, Nature, EMNLP, CVPR, ICCV, ECCV, CoRL).
  • Proven real-world impact from your research, demonstrated through shipped products, improved user experiences, or other measurable benefits for diverse stakeholders.

What the JD emphasized

  • record of publications in top-tier scientific venues
  • Proven real-world impact from your research, demonstrated through shipped products, improved user experiences, or other measurable benefits for diverse stakeholders.

Other signals

  • integrating rigorous scientific methods into the product lifecycle
  • bridge between research and product
  • teaching, guiding, and tutoring colleagues without research backgrounds
  • sharing your research with others via a range of means, including publication