About The Position

AI has created an unprecedented opportunity to make work better for hundreds of millions of people. Microsoft’s productivity division is hiring Applied Scientists II to help ensure we maximize this amazing opportunity. Our scientists collaborate closely with people across Microsoft’s product teams and Microsoft Research to see their ideas realized in products and services like M365, M365 Copilot, Office AI, and Office Products (Excel, PowerPoint, Word, etc.). They also contribute back to the scientific community through peer-reviewed publications at top venues, scientific presentations, and beyond. We are looking for Applied Scientists II who are creative, self-driven, curious, people-oriented and comfortable defining a path through ambiguity towards high-level goals. Research areas of interest include but are certainly not limited to reinforcement learning, agentic systems multimodal modeling, post-training techniques and their application, human-centered artificial intelligence (AI), domain-specific large language model (LLM) applications (e.g. long-form writing assistance), personalization, computational social science, memory, agentic retrieval-augmented generation (RAG), real-time AI systems, collaborative AI, privacy-preserving AI, trustworthy AI, data-centric AI, AI flywheels, and multilingual AI. 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.

Requirements

  • 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.
  • 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.

Nice To Haves

  • 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.

Responsibilities

  • Defining, leading, and helping to conduct research projects that simultaneously advance the state-of-the-art and directly benefit Microsoft’s core productivity products.
  • Shape product direction by integrating rigorous scientific methods into the product lifecycle.
  • 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.
  • Teaching, guiding, and tutoring colleagues without research backgrounds in state-of-the-art techniques and research best practices.
  • 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.
  • Effectively communicating with product leaders (and often Microsoft researchers (MSR)) throughout the planning and execution of applied research projects, which often involves learning and teaching complex concepts.
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