AI/ML Engineer
I am currently working with a client that has recently combined its advanced clinical reasoning technology with a major national healthcare platform. Together, they are building the first AI‑native Healthcare Revenue Operating System - a connected platform that interprets full medical records, payer rules, and financial workflows to automate medical coding, billing, and follow‑up.
This client operates at national scale with real customers, substantial datasets, and established distribution channels. Their AI systems already support production workflows across the majority of major U.S. health systems, processing hundreds of millions of patient encounters annually, including:
- 180M+ claims
- 550M+ patient encounters
- 1.2B+ workflow actions and outcomes
This offers startup‑level ownership paired with enterprise‑level impact. If you want to build AI that ships, scales, and meaningfully improves healthcare operations, this is an ideal environment.
The Role
As an AI/ML Engineer, you will lead development of early‑stage, high‑impact AI/ML systems; own the internal ML development environment (instrumentation, benchmarking, experimentation); and bring scientific rigor into production so ideas transition quickly from research to validated pipelines.
You will collaborate closely with Research Scientists to make models production‑ready through clear handoff contracts, performance gates, and packaging standards - and work with ML Platform/Ops teams to support safe and scalable deployment.
Roles are open across several seniority levels, with a minimum expectation of 5+ years of software engineering experience, including 2+ years in AI/ML.
What You'll Do
- Build training and inference infrastructure for a fast‑moving research team, including experiment tracking and benchmarking.
- Design and develop scalable AI systems for retrieval, ranking, categorization, and generative AI over large‑scale unstructured healthcare data.
- Architect and operate AI/ML systems end‑to‑end: model selection, training, deployment, monitoring, and iteration.
- Translate complex business problems into scalable and explainable AI system designs.
- Define robust evaluation datasets, metrics, and validation strategies tied to measurable outcomes.
- Build ranking and triage models to determine how work is routed between AI agents and human operators.
- Develop feedback loops and data flywheels to continuously improve models in production.
- Partner with software engineering, product, clinical, and operations teams to ensure measurable business value.
- Prototype new AI capabilities from 0 → 1 and harden them for production.
- Mentor other AI/ML engineers and support best practices across modeling and deployment.
Role Levels
Roles span multiple levels, from mid‑level through staff:
- Level 2: Delivers complete end‑to‑end projects independently.
- Level 3: Leads larger, more complex projects and supports L2 engineers.
- Senior: Manages a portfolio of initiatives tied to major technical goals.
- Staff: Provides organization‑level technical leadership across multiple teams or initiatives.
Benefits
- Highly competitive compensation (salary + equity)
- Flexible PTO
- Comprehensive health benefits
- 401(k) matching
- Mission‑driven and collaborative environment
Hiring Flow
- Introductory call - background + mission alignment
- Technical deep dives - pseudo‑coding + systems design (no Leetcode)
- Final in‑person interview at one of the client's hubs (travel provided)
- References
- Offer
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