Engineering Manager, Machine Learning

About us: 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. What you’ll do 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. Lead rigorous experimentation and model evaluation, ensuring our LLM systems meet clinical-grade performance and reliability requirements. Work closely with our engineering team to integrate and scale models in production, optimize inference efficiency, and maintain strong observability and monitoring. Establish and champion best practices in modeling, code quality, reproducibility, and experiment design—helping define “what incredible looks like” for ML at an early-stage, mission-driven health tech company. Communicate technical work clearly to cross-functional partners and leadership, translating ML developments into strategic implications for the business and product. Recruit, cultivate, and inspire the next generation of technical talent as the team grows. What we look for Degree in computer science, mathematics, physics, or a related field. 7+ years of hands-on ML experience, ideally including LLMs or NLP; healthcare exposure is a plus but not required. 2+ years of technical leadership experience (formal or informal) where you’ve guided teams, set direction, and mentored others and 1 or more years formal management experience. Deep ML expertise: model development, training workflows, data pipeline design, evaluation methodology, and production deployment. Strong Python fluency and experience with modern ML tooling and infrastructure. Comfortable owning production-level data pipelines, monitoring, and performance analysis. A strategic thinker who can also dive deep into hands-on implementation when needed. Thrives in fast-paced, high-autonomy environments with evolving requirements. Excellent communication and collaboration skills. A passion for transforming healthcare with state-of-the-art AI. Would be nice Previous early stage startup experience (and a love for it) Expected c