Engineering Manager, Machine Learning

Layer Health is a healthcare technology company building an AI layer that synthesizes medical-record information to reduce friction in healthcare. The Engineering Manager, Machine Learning will lead and mentor ML engineering and science teams, shape ML strategy, and oversee the development, evaluation, deployment, and scaling of reliable clinical-grade LLM systems.

Responsibilities:

• 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