Company
Engineering
SeniorAI/MLEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior AI/ML Engineer. Skills: ML infrastructure, Model training, Inference serving. Design ML systems. Ship ML systems”
What You'll Achieve.
Measurable model improvements
Industry & Context.
Translate ambiguous goals
What They're Looking For.
Must Have
4+ years applied ML engineering, Hands-on experience with LLMs, Python and PyTorch fundamentals, Experience with distributed training
Nice to Have
JAX fundamentals, GPU optimization experience, Inference serving experience, Pragmatic about trade-offs
What You'll Do.
Own model performance
Build evaluation harnesses
Build offline benchmarks
How You'll Work.
Team & Collaboration
Work with product
Full Job Description
About the role Our client is a well-funded AI startup building production-grade ML infrastructure used by enterprise customers. They are looking for a Senior AI/ML Engineer to own model training pipelines, evaluation systems, and inference serving at scale. Full-time, on-site in San Francisco. WHAT YOU WILL DO - Design and ship end-to-end ML systems: data pipelines, training, evaluation, deployment - Own model performance, latency, and cost trade-offs in production - Build evaluation harnesses and offline benchmarks for fast iteration - Work directly with product to translate ambiguous goals into measurable model improvements - Mentor other engineers on ML best practices and code quality WHAT WE ARE LOOKING FOR - 4+ years of applied ML engineering in production environments - Hands-on experience with LLMs, fine-tuning, RAG, or large-scale recommender systems - Strong Python and PyTorch (or JAX) fundamentals - Experience with distributed training, GPU optimization, or inference serving - Pragmatic about trade-offs between research-grade and ship-grade work This role is presented by a recruiting partner. Company name shared after an initial conversation.
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