Machine Learning Engineer

Acceler8 Talent; San Mateo (CA); Hybrid; USD 275,000 - 350,000; Full time

Benefits offered by this job

Equity

Hybrid work (onsite 2-3 days)

Job summary

Acceler8 Talent is recruiting a Staff AI/ML Engineer in San Mateo, CA. The role focuses on enterprise AI agents, RAG, knowledge graphs, and production-grade AI systems. You will own major parts of the agent architecture, including reliability, retrieval, and code generation, with significant ownership over production AI agent infrastructure.

The position is hybrid with 2–3 days on-site. Base salary ranges from $275k to $350k, plus equity, reflecting level and experience, with strong enterprise

Job description

Staff AI/ML Engineer | Enterprise AI Agents | San Mateo, CA

I’m working with a well-funded Series B AI startup that’s building the intelligence layer behind a new generation of enterprise AI agents.

With $100M+ raised and already seeing significant adoption across major global enterprises, they’re now expanding the AI team responsible for agents that can understand complex company data, retrieve the right context, generate production-ready code and automatically recover when things go wrong.

They’re looking for an experienced Staff AI/ML Engineer to take ownership of major parts of the agent architecture across:

• Agentic AI & reasoning systems
• RAG & advanced retrieval
• Knowledge graphs & enterprise data
• Code generation
• Evaluation & benchmarking
• Production reliability & error recovery

The interesting challenge here isn’t simply getting an LLM to generate something that looks right.

It’s building AI systems reliable enough to generate real data workflows that some of the world’s largest enterprises can inspect, trust and deploy into production.

What’s on offer:

• San Mateo, CA — Hybrid, 2-3 days onsite
• $275k-$350k base + equity, calibrated to level
• $100M+ raised at Series B
• Significant enterprise adoption already in place
• Genuine ownership over production AI agent architecture

This would suit someone who has gone beyond experimentation with LLMs and has experience building and shipping production AI/ML systems, particularly across agents, retrieval, RAG, knowledge systems or code generation.