- Develop the PT2 compiler (TorchDynamo, TorchInductor, Export, PyTorch Core).
- Improve PyTorch performance via systematic solutions for the entire community.
- Explore the intersection of the PyTorch compiler and PyTorch distributed.
- Optimize Generative AI models across the stack (pre-training, fine-tuning, and inference).
- Conduct cutting-edge research on �ML compilers and ML distributed technologies.
- Collaborate with users of PyTorch to enable new use cases of PT2 technologies both inside and outside Meta.
- BS/MS in computer science or related field.
- Research or industry experience in compilers, ML systems, ML accelerators, HPC, GPU performance, and similar.
- Proficient in Python or CUDA programming
- 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.
- Ph.D in computer science, applied mathematics, or related fields.
- Familiarity with PT2 technologies, Triton, MLIR, or experiences working inside PyTorch.
- Expert knowledge in GPU performance and writing high-performance CUDA kernels.
- Research and software engineer experience demonstrated via fellowships, patents, internships, or coding competitions.
- First-authored publications at peer-reviewed conferences (e.g., NeurIPS, MLSys, ASPLOS, PLDI, CGO, PACT, ICML, or similar).
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