We do research on world models, reasoning, planning, memory, at scale. In particular, we aim at hard benchmarks in code generation, leveraging execution feedback. We are looking for a tech lead for significant engineering and research features to serve research needs across FAIR, and other organizations.
- Tech lead a state of the art research codebase on large language models, world models, reinforcement learning
- Full-stack development from integrating with kernel specialists to research trainings at scale
- Cross-org leadership (e.g. PyTorch)
Minimum Qualifications
- PhD in CS, Math, or AI
- Advanced knowledge of PyTorch
- knowledge of AI research codebases and workflows
Preferred Qualifications
- Expertise implementing CUDA or Triton kernels
About Meta
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