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Hybrid ML Engineer: Python, PyTorch, Distributed Training

Open 17d

Summary

Build and deploy production-grade ML models in San Jose, scaling distributed training across multi-GPU clusters and optimizing performance for low-latency serving.

Enigma is seeking an experienced Machine Learning Engineer in San Jose to drive the end-to-end lifecycle of production ML models. You will scale training across multi-GPU clusters, optimize performance and cost, and build robust serving systems with attention to latency and reliability.

You will work across Research, Platform/Infra, Data, and Product teams, applying distributed training techniques (DDP/FSDP/ZeRO) and modern tooling (Triton, vLLM, ONNX, TensorRT) to deliver production-ready

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