Principal ML Performance Engineer – GPU Optimization

Proxima is seeking a Principal ML Performance Engineer to optimize training and inference for structural and generative models, with a focus on CUDA, Triton, and distributed training across large GPU clusters. You will profile bottlenecks, write efficient kernels, and drive multi-node scalability.

As a senior leader, you will scale training across 32–64 nodes, reduce inference costs on thousands of GPUs, and mentor engineers while defining technical direction for the team.

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