Whoop!

Technical Program Manager

• Own end-to-end program management for core algorithm development initiatives, from early research and data collection through model development, validation, and production deployment
• Partner with leadership to translate algorithm and sensing strategy into executable program plans with clear milestones, dependencies, risk profiles, and success criteria
• Plan and manage algorithm development timelines with full awareness of cross-functional dependencies across data collection, signal processing, software, firmware, and product teams
• Drive cross-functional alignment by working directly with product managers, engineering leads, and data collection groups 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
• 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

Senior Technical Program Manager, Core Algorithms

Machine Learning Engineer

• Create, improve, and maintain production services that provide analysis for health features in collaboration with data scientists and MLOps engineers
• Collaborate with data engineers to improve ML data pipelines, tooling, and validation systems that support robust model performance
• Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency and cost efficiency
• Collaborate with researchers and product teams to align model development with physiological insights and member impact
• Participate in on-call rotations for data science services, ensuring uptime and performance in production environments

Senior Machine Learning Engineer, Insights

Team Lead

• Manage a team of 10–15 Membership Services Representatives with varying schedules.
• Identify training and development opportunities and partner with L&T, QS, and Content teams to implement targeted development plans and resources.
• Conduct regular 1:1s, team meetings, and coaching sessions in line with established standards.
• Build, develop, and lead a high-performing team that meets or exceeds defined performance goals and KPIs.
• Engage and develop direct reports by fostering an open, collaborative environment, providing individualized coaching and growth plans, and driving needs-based initiatives through effective communication, feedback, and best-practice sharing.
• Manage HR-related issues appropriately and in accordance with company guidelines.
• Conduct regular shadowing sessions with the team to ensure quality, consistency, and efficiency.
• Review emails and escalated member issues within an acceptable time frame & interact directly with members when necessary.
• Follow company guidelines while thinking quickly and creatively to offer solutions that meet member needs.
• Stay on top of all administrative responsibilities, ensuring accurate, timely completion of required workflows, reporting, documentation, and internal updates.
• Maintain in-depth knowledge of processes and procedures, supporting team questions and providing approvals as needed.
• Create and maintain a positive, inclusive, and motivating team culture.
• Leverage AI-driven tools and insights to improve team efficiency, enhance member experience, and support data-informed coaching and decision-making.
• Support cross-functional and department-wide projects by providing team insights, executing operational tasks, and helping drive successful implementation.

Membership Services Team Lead – Overnight

Membership Services Team Lead

• Create, improve, and maintain production services that provide analysis for health features in collaboration with Data Scientists and MLOps Engineers
• Collaborate with Data Engineers to improve ML data pipelines, tooling, and validation systems that support robust model performance.
• Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency.
• Collaborate with researchers and product teams to align model development with health insights and member impact.
• Participate in on-call rotations for data science services, ensuring uptime and performance in production environments.

Senior Machine Learning Engineer, Health

Medical Director

• Own the clinical evidence strategy across WHOOP’s portfolio of regulated and unregulated health features, including feasibility, validation, regulatory submission, launch, and post-market evidence generation.
• Translate product concepts and algorithms into clinically meaningful indications, claims, endpoints, and evidence strategies.
• Define clinical validation strategies, including study design, comparator selection, endpoint development, sample size justification, statistical analysis planning, success criteria, and evidence requirements.
• Lead the design and oversight of feasibility, validation, and post-market studies supporting product development and regulatory objectives.
• Lead clinical strategy and evidence development for FDA, CE Mark, and other regulatory pathways, including participation in regulatory interactions and review of clinical content for submissions.
• Develop, review, and approve key clinical deliverables, including protocols, CRFs, SAPs, CSRs, CERs, and regulatory submission content.
• Serve as the clinical and scientific subject matter expert for internal stakeholders, regulators, investigators, advisors, and external partners.
• Partner closely with Product, Data Science, Engineering, Regulatory, Quality, Legal, and Commercial teams to ensure clinical evidence informs product, regulatory, and business decisions.
• Build and lead a high-performing Clinical Science organization, including hiring, mentoring, workforce planning, and establishing scalable processes, standards, and operating models.
• Communicate complex scientific, clinical, and regulatory concepts to technical and non-technical stakeholders, including executive leadership.

Director, Clinical Science

• Lead the clinical operations function responsible for executing studies that support WHOOP’s regulated and unregulated health features.
• Own operational strategy and study execution across the product lifecycle, from early concept and feasibility through validation, regulatory submission, launch, and post-market evidence generation.
• Oversee studies conducted through CROs as well as internally executed studies, ensuring high-quality execution across WHOOP’s clinical portfolio.
• Build and mentor a high-performing Clinical Operations organization.
• Strengthen WHOOP’s clinical operations capabilities and ensure our study execution strategy meets the expectations of regulators, investigators, participants, and the business.

Director, Clinical Operations

• Lead the cloud ML team responsible for the algorithms powering sleep, recovery, and training
• Directly manage applied ML scientists and ML engineers; provide coaching, career development, and performance feedback that grows individual contributors into strong technical leaders
• Ensure the technical quality bar for algorithm development is maintained by establishing the processes, reviews, and standards that guarantee rigor from research through deployment, and diving into designs and architectural decisions where necessary
• Help drive the vision for what WHOOP algorithms and next-generation sensors can enable; advocate for member experience and push the boundaries of what our data makes possible
• Ensure cloud algorithms remain compatible with future hardware generations; partner with Sensor Intelligence and Hardware to evolve proof-of-concept algorithms that leverage new sensor capabilities and bring them to production readiness
• Establish and improve development lifecycle practices: experiment management, model validation, deployment pipelines, and production monitoring
• Partner with ML Platform / MLOps to define requirements and drive maturity improvements across experiment tracking, model monitoring, deployment automation, and observability
• Drive cross-functional alignment with Sensor Intelligence, Product, Software Engineering, and Research teams

Associate Director, Machine Learning – Core Algorithms

Community Manager

• Lead day-to-day community engagement across Instagram, TikTok, LinkedIn, X, Reddit, and emerging platforms, fostering authentic relationships with members, athletes, creators, partners, and prospective customers.
• Develop and execute platform-specific community engagement strategies that drive audience growth, participation, advocacy, and brand affinity.
• Partner cross-functionally to activate community engagement around product launches, partnerships, campaigns, athlete moments, and key cultural events.
• Monitor community sentiment, social conversations, and emerging trends, surfacing actionable insights and recommendations to stakeholders across Marketing, Product, Customer Experience, and other teams.
• Establish feedback loops that elevate member perspectives, product feedback, and recurring community themes to inform decision-making across the organization.
• Track and analyze engagement, sentiment, and community health metrics, using performance insights to continuously optimize community strategies and initiatives.
• Serve as a subject matter expert on social platform best practices, internet culture, and community trends, identifying opportunities for WHOOP to engage authentically and remain culturally relevant.