Engineering Manager, Machine Learning

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.

We’re seeking outstanding hires to join our team as early members. This is an opportunity to contribute to a high-impact, collaborative, mission-driven team, and help define the next stage of growth for Layer Health. Together, we will create the AI layer that will redefine healthcare for the better.

We’re currently looking to hire our first ML Engineering Manager to help mentor our team and oversee ML strategy. This is a hybrid role in our Boston or NYC office; you will work closely with our engineers, ML scientists, and product teams to enable our team to build ML-native enterprise platforms, ensuring scalability, efficiency, and reliability.

Here’s a collection of articles about our product, mission, recent funding round, etc.

Provide technical leadership and management to a small, high-leverage team of ML Engineers, Research Engineers, and ML/Data Scientists. Act as a player-coach: you’ll set direction while remaining actively involved in design, experimentation, and implementation.

Drive the development of end-to-end ML systems—from shaping ambiguous problems into clear model requirements, training datasets, evaluation frameworks, and model architectures, to supporting reliable production deployment.

Help craft and drive the ML technical agenda in partnership with engineering, research, and product leadership, ensuring the roadmap aligns with company goals and high-impact opportunities.