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 is critical to ensuring those efforts are executed with the rigor, coordination, and pace required to deliver world-class health products.
As a Senior Technical Program Manager, you will serve as the connective tissue across the cross-functional teams required to bring health algorithms from research through validation to production. You will work directly with machine learning engineers and applied ML scientists developing the health algorithms. You will coordinate cross-functionally with product managers, regulatory and quality teams, clinical scientists, software engineers, and firmware engineers to plan, track, drive delivery of complex, multi-disciplinary health programs.
Success in this role requires a deep understanding of the ML development lifecycle in order to anticipate risks, ask the right questions, and ensure that decisions are made with the appropriate technical context. You will also leverage and build AI-powered tools and workflows to increase the speed, visibility, and rigor of program execution.
RESPONSIBILITIES:
Own end-to-end program management for health algorithm development initiatives, from early research and data collection through model development, validation, regulatory submission, and production deployment
Partner with leadership to translate health feature strategy into executable program plans with clear milestones, dependencies, risk profiles, and success criteria
Plan and manage ML development timelines with full awareness of cross-functional dependencies across data engineering, clinical, regulatory, quality, software, firmware, and product teams
Drive cross-functional alignment by working directly with program managers and leads on partner teams to ensure shared understanding of priorities, timelines, and deliverables
Proactively identify future risks, obstacles, and dependencies before they become blockers; develop and drive mitigation plans
Report program status, risks, and key decisions to leadership with clarity and precision; flag issues early and with proposed solutions
Facilitate and maintain program governance including planning cadences, design reviews, decision forums, and cross-team syncs
Oversee health data governance workflows relevant to ML development, including data collection, labeling, dataset management, and data quality processes
Build and continuously improve AI-enabled tools, workflows, and automations to increase program management effectiveness, including status tracking, dependency mapping, risk monitoring, and stakeholder communication
QUALIFICATIONS:
5+ years of experience in an ML role or technical program management, with direct experience supporting AI/ML, data science, or algorithm development teams
Demonstrated understanding of the ML development lifecycle, including data collection, model training, evaluation, validation, and deployment
Experience with developing algorithms for Software as a Medical Device (SaMD), medical device development, or other regulated product development (FDA, IEC 62304, ISO 13485, ISO 14971)
Fluency with AI tools (e.g., LLMs, automation platforms, workflow builders) and a demonstrated track record of building or adopting AI-powered workflows to increase speed and scale of program execution
Ability to understand technical concepts deeply enough to identify risks, ask critical questions, and facilitate resolution of blockers across ML, data, software, and regulatory workstreams
Clear, confident communicator who can bridge deeply technical ML teams and business, regulatory, and clinical stakeholders
Data-driven approach to program planning and tracking, comfortable defining and reviewing metrics to measure program health and success
