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Senior AI/ML Engineer

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...

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Clera (ashby) San Francisco, California, United States Source published Jun 3, 2026 Verified 52 minutes ago
✓ 80% verification score · Source: Clera (ashby) · Always confirm final requirements on the original source.
Complete source information imported The available role or programme description, requirements, benefits and source facts were imported from the public official endpoint and formatted for reading.
EmploymentFull Time
CountryUnited States
DepartmentEngineering

Overview

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) fundamen

Full job description

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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Verification notes

Discovered directly from the employer’s public Ashby Job Postings API. The complete public role content and compensation metadata were normalized into safe candidate-facing sections.

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