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
Minimum Qualifications
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer 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, Computer Vision (3D), Physical AI, 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: 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 country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
- 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)
- This position will require knowledge of post-training for LLMs using reinforcement learning techniques. It will also involve novel modalities such as 3D and engineering domain-specific simulators, so computer vision expertise in 3D is welcome as well
- Experience integrating and debugging prototype/scientific software-hardware systems including mechanical, aerospace, or civil engineering domain-specific simulation
- Experience working and communicating cross-functionally in a team environment
- Prior work experience in the fields of mechanical, aerospace, civil engineering or other engineering domains
$122,000/year to $181,000/year + bonus + equity + benefits
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