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Software Engineer, ML Efficiency

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The role

Enable the team to develop large-scale end-to-end driving models with high hardware efficiency, reliable training and inference, and a great developer experience.
Participate in model design from a hardware-efficiency perspective to boost performance and scalability.
Collaborate with internal and partner teams to advance ML infrastructure and tooling for scalable workloads.
Drive system performance improvements through parallelism, buffering/prefetching, pipelining, and asynchronous execution.
Implement and optimize using Python and ML frameworks (PyTorch/JAX/TensorFlow) and accelerator programming (CUDA, Triton).
Candidates should have a BS in Computer Science or related field, strong software engineering skills, and experience with large-scale reliability and C++.

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