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Microsoft Corporation Logo Microsoft Corporation · IT - Software Development

Research Engineer - Generative AI - AI Frontiers

United States, Redmond 100600.00 - 199000.00 USD / Year · Job Posted April 11, 2026
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Job Description

The AI Frontiers lab at Microsoft Research is charted with ambitious research goals for advancing Artificial Intelligence (AI) capabilities in several key areas including modeling, algorithms, reasoning and agentic AI. Our lab offers a vibrant environment for cutting-edge multidisciplinary research, including an open publication policy and close links to top academic institutions around the world. This Research Engineer position is a unique opportunity to contribute towards tackling some of the hardest and most rewarding challenges in AI. You will help develop novel ideas in bleeding edge reinforcement learning research as well as help evolve our pre-training, mid-training, and post-training codebases that gave birth to famous models such as Phi establishing many new records. You will collaborate with researchers and engineers across many disciplines to help advance the state of the art in reasoning and agentic AI.

Job Responsibility

  • Design, develop, execute, and implement technology research projects in collaboration with other researchers, engineers, and product groups
  • Be a part of research breakthroughs in the field and play a crucial role in developing, improving, and exploring the capabilities of Large Language Models (LLMs), reasoning and agentic AI
  • Embody our culture and values

Requirements

  • Bachelors in Computer Science or relevant field AND 2+ years related experience
  • OR Master's Degree in Computer Science or related field AND 1+ year(s) related experience
  • OR Doctorate in Computer Science or related field
  • OR equivalent experience
  • 1+ year(s) experience developing with Python and Pytorch/JAX

Nice to have

  • Familiarity with architecture and optimizations for large language models
  • Hands-on work in debugging and profiling Pytorch distributed code
  • Basic understanding of working of CUDA kernels
  • Familiarity with pre-training, mid-training and/or post-training pipelines for language and/or multimodal models
  • Foundational understanding of reinforcement learning and key challenges in the field
  • Experience with verl, Ray, Megatron and/or vLLM is a significant plus
  • Any experience in building scalable services can be highly complementary
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