Hire Top ML Engineers in San Francisco

San Francisco is the world's deepest ML engineering talent pool, shaped by OpenAI, Anthropic, Google Brain, Meta FAIR and a long tail of frontier-model startups. GitHunt ranks SF ML engineers by their real GitHub contributions.

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🎯 Find ML Engineers in San Francisco

Search our database of 100M+ GitHub developers to find elite ML Engineers in San Francisco.

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Why Hire ML Engineers in San Francisco?

🎯
Hire engineers with direct production experience training, fine-tuning and deploying large models at frontier-lab scale - very few markets globally have comparable depth.
💼
Tap deep PyTorch, JAX, CUDA and inference-infrastructure talent, with significant overlap with vLLM, TensorRT-LLM, Triton and modern serving stacks.
🚀
Source ML engineers with strong OSS profiles - many SF ML ICs are maintainers on PyTorch, transformers, vLLM, Flash Attention and the core training stack.

About ML Engineers

Senior ML engineers in SF own training pipelines, fine-tuning workflows, inference infrastructure, or model evaluation systems. The strongest SF ML candidates have shipped production model serving at scale and have meaningful contributions to OSS training or inference frameworks.

The SF ML ecosystem has bifurcated: pure ML engineers (training, MLOps, evaluation) versus AI/LLM-application engineers. GitHunt's role-aware scoring distinguishes these directly via commit fingerprints on PyTorch, vLLM, Ray, transformers versus LLM-app frameworks.

Market Insights: ML Engineers in San Francisco

The 2026 SF ML engineering market is extreme: senior ML engineers with shipped frontier-model training or inference experience command $300k-$500k base plus heavy equity. Mid-level production ML engineers sit at $200k-$280k base.

LinkedIn captures very little of the strongest SF ML talent - many key ICs are quiet OSS contributors to PyTorch core, vLLM, Flash Attention, FlashInfer, or Ray. GitHunt indexes their commit history directly and ranks by exact role and stack match.

Use GitHunt to find SF ML engineers in days, with verified contributions to the production ML stack you actually use.

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