layerhealth · Boston or NYC
Skills: Python
Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology. Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health’s diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine. Here’s a collection of articles about our product, mission, recent funding round, etc. Job Description You will work with the Layer Health ML team applying our existing ML workflow to tailor models for a specific clinical use case. You will design, build, evaluate, and iterate on these models — combining strong data science fundamentals with modern LLM techniques to deliver high-accuracy, production-ready solutions across new clinical domains. This is a high-velocity, high-ownership role for someone who enjoys diving deep into error modes, making targeted improvements, and closing the loop between model performance and real-world impact. This contract will require full-time hours. What you’ll do: Own end-to-end development of models for specific use cases: Build and iterate using our ML/LLM-powered workflows for new clinical areas, from initial prototyping through production refinement. Conduct evaluation & error analysis: Own rigorous evaluation of model performance; perform deep error analysis to identify systematic failure modes and drive targeted improvements. Ship frequent, high-quality updates to models based on data, feedback, and observed edge cases. Leverage LLM application & tooling: Apply modern LLM techniques (prompting…
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