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Research Scientist Intern, FAIR - Physical Engineering AI (PhD)

Meta· Research
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Hybrid (Seattle, WA)$7.7k/mo - $12.7k/moInternPosted 4d ago

About the role

Meta FAIR internship focused on physical engineering AI, combining heavy software research engineering with large-scale data manipulation and simulator integration to advance LLM post-training and physics-based AI for engineering domains.

Responsibilities

  • Explore and develop novel post-training paradigms for LLMs using reinforcement learning.
  • Explore and develop novel LLM post-training recipes using 3D data.
  • Integrate large-scale simulation into LLM post-training.
  • Explore mechanical, aerospace, civil, and other engineering disciplines and how to enable LLMs to solve key problems in these domains.
  • Brainstorm with research mentors, review literature and existing solutions of a challenging real-world research problem.
  • Develop novel solutions, implement prototypes, and perform extensive experiments to test the proposed solutions in meaningful benchmarks and metrics, analyze the results and verify the conclusions.
  • Draft and polish research reports and/or publications.
  • Present research outcomes to internal and/or external audiences.
  • Contribute research that can be applied to Meta product development.

Qualifications

  • Currently has or is in the process of obtaining a PhD degree in Artificial Intelligence, Physical AI, Computer Vision (3D), Machine Learning, Computer Science, Computer Engineering, Mechanical Engineering, Electrical Engineering, relevant technical field, or equivalent practical experience
  • Research and/or work experience in at least one of the following research areas: physical AI, simulation, reinforcement learning, representation learning, self-supervised learning, multimodal learning, robotics policy development, computer vision (3D), egocentric perception, embodied AI and/or LLMs, control theory, optimization algorithms
  • Experience in C/C++ and Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Skills

Required:Post-training paradigms for LLMs using reinforcement learningLLM post-training with 3D dataLarge-scale simulation integrationC/C++ and PythonDeep learning frameworks (PyTorch, TensorFlow)
Nice to have:Mechanical, aerospace, civil engineering domain knowledge

Benefits

  • In addition to base compensation, Meta offers benefits
Last updated Oct 23, 2026. Interested? Apply on the company site.

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