Applied Researcher 2/ Senior Applied Researcher

Microsoft Microsoft · Big Tech · Redmond, WA +4 · Research Sciences

Applied Researcher role focused on post-training code specific models and agentic research for developer tools like Github Copilot and VS Code. The role involves building and managing large-scale ML experiments, creating new datasets, and collaborating with product teams to take research from concept to product.

What you'd actually do

  1. Contribute projects on the future of AI for developers.
  2. Collaborate across disciplines with product teams across Microsoft and Github.
  3. Stay up to date with the research literature and product advances in AI for software engineering.
  4. Create new datasets from both the world's public code and Microsoft's internal data.
  5. Build and manage large-scale ML experiments and models.

Skills

Required

  • Master's Degree in relevant field AND 1+ year(s) related research experience OR Bachelor's Degree in relevant field AND 2+ years related research experience OR equivalent experience.

Nice to have

  • Doctorate in relevant field OR Master's Degree in relevant field AND 3+ years related research experience OR Bachelor's Degree in relevant field AND 5+ years related research experience OR equivalent experience.
  • 3+ years of research/industrial experience with LLM
  • Industrial/research experience with CodeLLM, Code agent or AI IDE
  • Experience participating in a top conference in relevant research domain
  • Experience publishing academic papers as a lead author or essential contributor.

What the JD emphasized

  • post-training code specific models
  • agentic research for Copilot Coding Agent
  • apply and advance existing approaches of using LLMs for software engineering
  • run experiments, evaluate, iterate, and improve your AI projects on a large scale
  • Experience publishing academic papers as a lead author or essential contributor.

Other signals

  • post-training code specific models
  • agentic research for Copilot Coding Agent
  • apply and advance existing approaches of using LLMs for software engineering
  • run experiments, evaluate, iterate, and improve your AI projects on a large scale