Senior Manager, Machine Learning, SaMD

Location: Boston, MA Workplace: OnSite 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. You will be accountable for both the engineering velocity of your teams and the rigor required to operate inside a regulated medical device development environment (FDA, IEC 62304, ISO 13485, ISO 14971). 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. 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 seniorICs, 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. QUALIFICATIONS: - 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. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $170,000 - $230,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.   In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.   These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.   Learn more about WHOOP https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg.