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Research Scientist, AI for Reasoning

France, Paris · Job Posted March 25, 2026
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Job Description

Meta is seeking a Research Scientist to join its Fundamental AI Research (FAIR) organization, focused on making significant advances in LLMs reasoning, using reinforcement learning, synthetic data generation and advanced scaffolding/agentic techniques, partially with a focus on formal and informal maths, to join our Paris site. You will have the opportunity to work with a broad and highly interdisciplinary team of scientists, engineers, and cross-functional partners, and will have access to cutting edge technology, important resources, and research facilities.

Job Responsibility

  • Lead, collaborate, and execute on research that pushes forward the state of the art in reasoning research, with an initial focus on formal and informal mathematical
  • Work towards long-term high-stakes research goals, while identifying intermediate milestones
  • Directly contribute to experiments, including designing experimental details, implement reusable code, running evaluations, and organizing results
  • Contribute to publications and open-sourcing efforts
  • Mentor other team members. Play a significant role in healthy cross-functional collaboration

Requirements

  • Currently has or is in the process of obtaining a PhD in the field of Computer Science, Mathematics, or similar quantitative field
  • Experience training and evaluating large models on State-of-the-Art codebases and developing new architectures, losses and training recipes
  • First-author publications at peer-reviewed AI conferences (e.g. NeurIPS, ICML, ICLR)
  • Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use
  • Experience working with SOTA Reinforcement Learning codebases and familiarity with one or more machine learning frameworks (e.g. pytorch, VERL, …)
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Nice to have

  • Familiarity with the Lean 4 language and ecosystem and mathematical expertise
  • Experience with communicating complex research for public audiences of peers
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