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.

Requirements

Must-haves

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
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpython

Platform: ashby
Effort: quick