Senior Manager, Machine Learning

Whoop•Boston, MA

3d•$170,000 - $230,000•Onsite

About The Position

WHOOP is on a mission to unlock human performance and healthspan. Our Health Machine Learning team develops the algorithms and models that power health features used by millions of members. This role exists to scale that work: building and leading the engineering and science teams that bring SaMD products from research through validation, submission, and production deployment. As a Senior Manager, SaMD, you will own delivery and people outcomes across the machine learning engineers and applied ML scientists developing WHOOP's regulated health features. You will set direction for your teams, develop the next generation of leaders within the function, and partner deeply across regulatory, quality, clinical science, product, software, and firmware to deliver health products that meet a clinical-grade bar. Success in this role requires a profile with both ML and SaMD depth to evaluate your team's most important decisions, plus the people leadership skill to grow ICs, drive cross-functional alignment, and deliver with both pace and rigor in a regulated environment.

Requirements

7+ years of experience in ML, applied science, or software engineering, with 3+ years managing engineering and/or science teams
Bachelor's degree in Computer Science, Engineering, Applied Math, Biomedical Engineering, or a related field
Demonstrated track record junior and senior ICs, including hiring, performance management, and developing people who in turn raise the bar around them
Deep familiarity with the ML development lifecycle: data collection, model training, evaluation, validation, deployment, and monitoring, sufficient to evaluate the most important technical and methodological decisions your team makes
Direct experience shipping algorithms or ML-enabled software in a regulated environment (Software as a Medical Device, medical device development, or comparable QMS-controlled product development under FDA, IEC 62304, ISO 13485, ISO 14971)
Fluency operating across regulatory, quality, and clinical stakeholders, including familiarity with V&V, traceability, change control, design history, and audit readiness in fast-moving ML programs
Demonstrated ability to set strategy and make timely prioritization calls under uncertainty, keeping the team focused on the highest-leverage work
Demonstrated AI-tooling sophistication: a track record of building or adopting AI-enabled workflows that materially improved team speed, quality, or decision confidence
Clear, high-signal communicator who can move fluidly between deeply technical ML/regulatory discussions and executive-level summaries of risk, trade-offs, and direction.

Responsibilities

Own delivery, team health, and people outcomes across multiple workstreams within ML SaMD team
Translate department strategy into clear quarterly plans, milestones, and success criteria; align the team on the highest-leverage work and adapt deliberately as the business evolves
Build the team: lead hiring at scale, calibrate the bar for regulated development, and shape onboarding, leveling, and growth practices
Develop the next layer of leadership, coach junior and senior ICs, manage performance with clarity and care, and create the conditions for people to operate above their level
Set the standard for how regulated ML gets built at WHOOP: methodology, work quality, validation rigor, and audit readiness
Partner directly with regulatory, quality, product, software, and firmware leaders to align on roadmap, dependencies, and submission timelines; broker trade-offs between iteration speed and regulatory rigor
Own the risk posture for your function; anticipate execution, technical, and regulatory risks, design mitigation into the operating model, and keep senior leadership clearly informed of the most consequential decisions
Define and own the operating model for your function; planning cadences, design reviews, decision forums, data governance, and quality gates appropriate to a SaMD context
Build and continuously raise AI-enabled workflows that create measurable leverage across the team; for development, evaluation, documentation, traceability, and stakeholder communication
Represent the team's work credibly to executive and cross-functional audiences with brevity, evidence, and clarity.