Company
Engineering
SeniorMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Machine Learning Engineer. Skills: ML systems, Model training, Inference serving. Design ML systems. Ship ML systems”
Industry & Context.
What They're Looking For.
Must Have
4+ years of applied ML engineering, Python fundamentals, PyTorch fundamentals
Nice to Have
JAX fundamentals, Distributed training experience, GPU optimization experience, Inference serving experience
What You'll Do.
Own model performance
Build evaluation harnesses
Build offline benchmarks
Translate goals into improvements
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.
Applying for this Senior Machine Learning Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Ashby
- Ashby is a fast modern ATS — most applications take under 3 minutes.
- The resume parser is strong; verify parsed experience dates and job titles.
- Custom screening questions are often scored algorithmically — answer completely.
- Location field affects geo-based screening; use your actual metro area.
ANONYMOUS · UNFILTERED
What do employees actually say about this company?
Real rants from real employees. Read before you apply.