Senior Machine Learning Engineer

What you'll do

• Build benchmarking and evaluation frameworks for model latency, throughput, cost efficiency, and behavior.
• Optimize inference through techniques such as quantization, batching, caching, compilation, and runtime tuning; integrate models with distributed infrastructure.
• Improve deployment workflows and collaborate with product and engineering teams to deliver scalable AI capabilities; mentor engineers and contribute to technical direction.

What they ask for

• Experience building, optimizing, and operating machine learning models in production environments.
• Proficiency with Python and modern ML frameworks such as PyTorch, TensorFlow, or JAX, or equivalent.
• Hands-on experience with inference optimization techniques for large-scale models.
• Strong understanding of production ML evaluation, monitoring, regression management, rollout safety, and reliability.

Nice to have

• Experience with inference serving frameworks or runtimes such as SGLang, vLLM, TensorRT-LLM, ONNX Runtime, Triton, or llama.cpp.
• Experience contributing to open-source ML tooling, model serving frameworks, or inference runtimes.

Pay

$194,000 - $266,000 USD annual base salary (Bay Area); $185,000 - $254,000 USD annual base salary (New York City, New Jersey, Washington, Washington DC, and California excluding Bay Area)

Tools

Python, PyTorch, TensorFlow, JAX, SGLang, vLLM, TensorRT-LLM, ONNX Runtime

AI focus

Production ML inference for LLMs, speech, vision, and other models, including benchmarking, evaluation, inference optimization, and deployment at Internet scale.