Applied Scientist- II

Microsoft Microsoft · Big Tech · Bengaluru, KA, IN +1 · Applied Sciences

Applied Scientist II role focused on fine-tuning frontier LLMs for enterprise data, enabling task-specific agents and solutions. The role involves research in LLM post-training, particularly reinforcement learning for long-horizon dynamic workflows, and driving research into product capabilities for M365 Copilot.

What you'd actually do

  1. Train and deploy Language Models adapted to specific industry needs.
  2. Create and adapt novel training and fine-tuning algorithms for language models with special focus on reinforcement learning reinforcement learning for long-horizon dynamic workflow.
  3. Research innovation and scholarly dissemination: conceive and execute research projects that advance training methodologies; write and submit peer‑reviewed papers or preprints; and present work at conferences.
  4. Drive end‑to‑end translation of research into product capabilities, leading projects from ideation and prototyping through production integration and measurable customer impact.

Skills

Required

  • Python
  • PyTorch
  • training/fine tuning AI/ML models
  • Generative AI pipelines
  • RAG (Retrieval augmented generation)

Nice to have

  • multi-agent training in dynamic harness
  • training or contributing to the development of very large-scale language models (e.g., 100B+ to trillion-parameter models)
  • distributed training
  • async RL
  • long sequence handling

What the JD emphasized

  • reinforcement learning for long-horizon dynamic workflow
  • research innovation and scholarly dissemination
  • end-to-end translation of research into product capabilities

Other signals

  • fine-tune frontier LLMs
  • task-specific agents
  • LLM post-training
  • reinforcement learning for long-horizon dynamic workflow
  • research innovation and scholarly dissemination
  • end-to-end translation of research into product capabilities