AI / ML Engineer (LLM Optimization & AI-Driven Workflows)

BiomichealthSan Francisco, CA, United States

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Legion Health | AI-Driven Psychiatric Care – We’re Hiring!

Join us in building the most efficient, AI-powered mental healthcare system.

We’re a YC-backed company revolutionizing telepsychiatry—not with AI for diagnostics, but with AI-driven operations that actually make patient care faster, smoother, and more accessible.

We’re hiring top-tier engineers who thrive in high-velocity, AI-first environments and want to build technology that meaningfully improves lives. If you love shipping fast, working with AI, and solving hard problems, keep reading.

Overview

Why This Role?

You’ll work on practical AI deployment—optimizing LLM-powered workflows for real-world mental healthcare.
You’ll refine AI models that improve scheduling, risk assessment, and revenue cycle automation.
You’ll optimize feedback loops to improve LLM-driven decisions over time.
You’ll shape a real-world reinforcement learning approach that trains AI on provider feedback.

Responsibilities

Optimizing LLM workflows (fine-tuning models, prompt engineering, integrating feedback loops).

Improving AI explainability—building systems that show providers why AI makes certain recommendations.

Implementing retrieval-augmented generation (RAG) for more accurate, context-aware AI responses.

Building tooling to measure AI override rates, decision accuracy, and improvement metrics.

Working closely with clinicians to ensure AI improves their efficiency—not replaces them.

You’ll work on practical AI deployment—optimizing LLM-powered workflows for real-world mental healthcare.

You’ll refine AI models that improve scheduling, risk assessment, and revenue cycle automation.

You’ll optimize feedback loops to improve LLM-driven decisions over time.

You’ll shape a real-world reinforcement learning approach that trains AI on provider feedback.

Qualifications

3+ years experience in AI / ML engineering

Strong Python & ML background (LLMs, NLP, PyTorch / TensorFlow)

Experience with reinforcement learning (or curiosity to implement RL-based workflows)

Comfortable with production AI deployment (vector databases, API integrations, etc.).

Interest in AI for healthcare (compliance / security mindset preferred).

Benefits

$130-180K salary + 0.4-1.2% equity

Real AI autonomy—you won’t just be fine-tuning prompts, you’ll be shaping LLM-driven patient care workflows

Work at the bleeding edge of AI deployment in healthcare

A mission with impact—we’re solving real problems that affect millions of patients.

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Optimization Engineer • San Francisco, CA, United States