Manager, Machine Learning

Layer Health • Boston, MA

1d • $250,000 - $275,000 • Hybrid

About The Position

Layer Health is hiring its first ML Engineering Manager to mentor the team and oversee machine-learning strategy. This hybrid role is based in the company’s Boston or NYC office and works closely with engineers, ML scientists, and product teams to build scalable, efficient, and reliable ML-native enterprise platforms. The manager will provide technical leadership to a small team of ML Engineers, Research Engineers, and ML/Data Scientists, working as a player-coach who sets direction while contributing to design, experimentation, and implementation.

The role leads development of end-to-end ML systems, from defining model requirements and creating training datasets and evaluation frameworks to selecting model architectures and supporting reliable production deployment. In partnership with engineering, research, and product leadership, the manager will shape the ML technical agenda and align the roadmap with company goals. The role also emphasizes rigorous evaluation of LLM systems against clinical-grade performance and reliability requirements, production integration and scaling, inference efficiency, observability, and monitoring.

The manager will establish best practices for modeling, code quality, reproducibility, and experiment design; communicate technical work and its business and product implications to cross-functional partners and leadership; and recruit, develop, and inspire technical talent as the team grows. Layer Health is an early-stage healthcare technology company building AI to synthesize information from medical records and reduce friction in healthcare.

Requirements

• Degree in computer science, mathematics, physics, or a related field.
• 7+ years of hands-on machine-learning experience, ideally including LLMs or NLP.
• 2+ years of technical leadership experience, formal or informal, guiding teams, setting direction, and mentoring others.
• At least 1 year of formal management experience.
• Deep expertise in model development, training workflows, data pipeline design, evaluation methodology, and production deployment.
• Strong Python fluency and experience with modern ML tooling and infrastructure.
• Experience owning production-level data pipelines, monitoring, and performance analysis.
• Ability to combine strategic thinking with hands-on implementation.
• Comfort working in fast-paced, high-autonomy environments with evolving requirements.
• Excellent communication and collaboration skills.
• Passion for transforming healthcare with state-of-the-art AI.

Nice To Haves

• Healthcare exposure.
• Previous early-stage startup experience and enthusiasm for startup work.

Responsibilities

• Provide technical leadership and management to a small team of ML Engineers, Research Engineers, and ML/Data Scientists, while remaining involved in design, experimentation, and implementation.
• Drive development of end-to-end ML systems, including model requirements, training datasets, evaluation frameworks, model architectures, and reliable production deployment.
• Develop the ML technical agenda with engineering, research, and product leadership and align the roadmap with company goals and high-impact opportunities.
• Lead experimentation and model evaluation to ensure LLM systems meet clinical-grade performance and reliability requirements.
• Collaborate with engineering to integrate and scale production models, optimize inference efficiency, and maintain observability and monitoring.
• Establish best practices in modeling, code quality, reproducibility, and experiment design.
• Communicate technical work and its strategic implications to cross-functional partners and leadership.
• Recruit, develop, and inspire technical talent as the team grows.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager