AI Research Scientist, Physical AI

About the Role

Meta's Fundamental AI Research lab is seeking a Research Scientist to drive foundational research aimed at advancing physical AI capabilities. This role will involve heavy software research engineering, such as large-scale data manipulation and simulator integration.

Key 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

Requirements & Tech Stack

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, Mechanical Engineering, Electrical Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Currently has or is in the process of obtaining a PhD degree in Artificial Intelligence, Physical AI, Computer Vision (3D), Machine Learning, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Research 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)

Qualifications

• Experience integrating and debugging prototype/scientific software-hardware systems including mechanical, aerospace, or civil engineering domain-specific simulation
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, JMLR and Computer Vision (CVPR, ICCV, ECCV, TPAMI)
• Prior work experience in the fields of mechanical, aerospace, civil engineering or other engineering domains
• Experience working and communicating cross-functionally in a team environment