WHOOP is on a mission to unlock human performance and healthspan. Our AI/ML - Core Algorithms team develops the machine learning models and algorithms that power WHOOP's member-facing features, translating wearable data into actionable insights for millions of users. This role is critical to ensuring those efforts are executed with the coordination, rigor, and pace required to deliver world-class algorithmic products.

As a Senior Technical Program Manager, you will be embedded within the Core Algorithms (Cloud) team and serve as the connective tissue across the cross-functional teams required to bring algorithms from research through validation to production. You will work directly with machine learning engineers and applied ML scientists developing core algorithms. You will coordinate cross-functionally with product managers, signal processing engineers, software engineers, firmware engineers, and data collection groups to plan, track, and drive delivery of complex, multi-disciplinary algorithm programs.

This is not a traditional program management role. You need to understand the ML development lifecycle deeply enough to anticipate risks, ask the right questions, and ensure that decisions are made with the appropriate technical context. You will also be expected to leverage and build AI-powered tools and workflows to increase the speed, visibility, and rigor of program execution.

• 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

• 4+ years of experience in technical program or project 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

• 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 firmware workstreams

• Experience managing complex, multi-team programs with significant cross-functional dependencies

• Clear, confident communicator who can bridge deeply technical ML teams with product and business stakeholders

• Proven ability to drive alignment across diverse teams with competing priorities

• Data-driven approach to program planning and tracking, comfortable defining and reviewing metrics to measure program health and success

• Fluency with agile methodologies, sprint planning, and backlog management processes and associated tooling

• High ownership mentality with a bias for action and comfort operating in ambiguity

Preferred:




• Experience working in consumer health products or wearable technology

• Familiarity with algorithm development pipelines that depend on real-world physiological, health, or behavioral data