Staff Software Engineer, Machine Learning AI x Healthcare San Mateo (Hybrid)

We're working with a Series A startup based in San Francisco Bay Area that's transforming how AI powers healthcare - starting with automating complex voice-based workflows in the $400B revenue cycle management (RCM) industry.

Location: San Mateo, CA - 4 days/week in office

Comp: flexible - circa $220K-$350K base (experience dependent) + strong equity + top-tier benefits

Stage: Series A $19M raised 7-figure ARR

What They're Building

This is not another chatbot. The team is building agentic Voice AI - AI agents that sound human, handle edge cases gracefully, and navigate multi-turn phone interactions with insurance companies, providers, and other stakeholders.

Think: automated systems that actually complete tasks like prior authorization, eligibility checks, and credentialing - all over the phone.

️ The Role: Staff Software Engineer - ML

You'll be building the infrastructure that powers this AI agent fleet. This is not a research role - it's hands-on engineering work at the intersection of ML, infrastructure, and voice AI.

You'll own:

Orchestration logic that coordinates LLM agents in complex phone workflows
Backend systems that queue, dispatch, and audit high-volume, high-reliability calls
Fine-tuning and optimization of LLMs (LoRA, DPO, supervised learning)
Evaluation pipelines to benchmark performance of voice agents
New ML features and experimentation with tools like Langfuse, DSPy, Hugging Face

You Might Be a Fit If You

Have 5+ years of experience in backend or generalist software engineering
Have built and deployed ML/LLM-powered features in production
Have strong Python fundamentals and experience with orchestration tools
Have used Langfuse, DSPy, or Hugging Face for real-world LLM workflows
Are excited about building agentic systems - especially in the healthcare or voice domain
Want to join a no-juniors team of experienced engineers and build from scratch

Why you should apply:

Traction: Thousands of real calls per day, with major enterprise customers
Team: 20-person engineering team, median 10+ years experience
Product-market fit: Already achieved in a hard-to-crack space
Impact: Code ships to production fast and directly improves healthcare outcomes
Growth: Scale from 1 100 - you'll help architect the next generation

If you're interested in building production-grade AI agents that do real work in a high-stakes domain - and want to work alongside peers you'll learn from - drop me a message. Happy to share more!

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Staff Software Engineer, Machine Learning / LLM