Roles and Responsibilities :

- Design, build, and continuously improve production AI systems for complex healthcare workflows, including documentation, coding, denial management, appeals, and revenue cycle automation.

- Prototype new AI capabilities from 0 to 1, then harden them into reliable, explainable, auditable production systems with clear contracts, monitoring, evidence, and performance gates.

- Build rigorous evaluation and feedback loops using expert review, production logs, model outputs, and benchmarks to measure performance, regressions, reliability, cost, and business impact.

- Own outcomes end to end: understand the workflow, design the system, inspect failures, improve the system, and prove that the improvement matters.

- Set technical direction for a portfolio of projects, review designs, and mentor engineers as a technical lead.

- Partner with research, ML engineering, platform, and product teams on model selection, training, infrastructure, and Productionalization.

Skills Required :

- 5 - 10 years of Applied Research, ML engineering, research engineering, software engineering, or applied AI experience.

- A track record of shipping and operating production systems, ideally in ambiguous, high - stakes domains.

- Prior experience in healthcare, revenue cycle management, or other regulated industries is a plus, not a requirement.

Education :

- Bachelor's degree in computer science, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience.

- Master's or PhD in Computer Science, AI/ML, or a related field is a plus.