Engineering Manager, Machine Learning

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)

Compensation

Expected compensation range for this role is $250,000-275,000. Compensation is dependent on experience, overall fit to our role, and candidate location.