ML Model Evaluation Engineer

GROWTH PATH

This is an individual contributor role with strong ownership expectations. High performers may be considered for workstream lead or functional lead responsibilities after approximately 12 months, based on demonstrated ownership, delivery, technical judgment, mentoring, cross-functional influence, and ability to reduce dependency on the Director of ML.

ABOUT THE ROLE

We are looking for an ML Evaluation Engineer to own model quality, regression testing, release validation, and production impact analysis for clinical AI systems. This role sits between applied ML, clinical data, MLOps, and production operations.

Your job is to ensure that every model or workflow release is measurable, stable, and not degrading important clinical behavior. You will maintain evaluation datasets, create hidden test sets, run regression checks, analyze production issues, and produce release-readiness reports.

WHAT YOU WILL DO

- Build and maintain evaluation frameworks for clinical NLP, LLM, RAG, information extraction, and structured abstraction systems.

- Create and manage hidden test datasets that are not directly visible to model developers, reducing overfitting risk.…