Staff Applied AI Engineer

Staff Applied AI Engineer | Bay Area (Hybrid) | $200k–$298k base + equity

I’m partnering with a high-growth SaaS company at the cutting edge of AI and compliance on a senior Applied AI Engineer hire.

This is not a typical “build a model and ship it” role.

This is where you define what good AI looks like — owning how systems retrieve, reason, and deliver trustworthy outputs at scale.

You’ll sit at the intersection of research and real-world impact , shaping the intelligence behind core product features.

' :

• Improving RAG systems — retrieval quality, chunking, embeddings, hybrid search

• Designing evaluation frameworks (metrics, golden datasets, regression detection)

• Building and tuning ranking + reranking systems (cross-encoders, LLM rerankers)

• Running experiments to validate what actually improves performance

• Debugging failure modes across retrieval, reasoning, and generation

• Prototyping agent-style workflows over complex, document-heavy data

• Exploring ML approaches beyond GenAI (ranking, classification, probabilistic models)

' :

• 8–10+ years in applied ML, data science, or AI research

• Strong experience in information retrieval / search relevance

• Hands-on with RAG systems and retrieval optimization

• Deep understanding of evaluation + experimentation (A/B testing, metrics)

• Python + strong problem-solving / research mindset

• Someone who can explain why systems work (or don’t) — not just build them

:

• You’ve only used LLM APIs without optimizing retrieval or evaluation

• Your experience is purely prompt engineering

• You prefer purely academic research without product impact

• You’re looking for a heavily structured, slow-moving environment

Candidates must be based in the Bay Area and open to a hybrid setup .

If you’re interested in making AI systems measurably better — not just building them , drop me a message or comment below.

Happy to share more details confidentially.

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