Senior Technical Program Manager, Core Algorithms
whoop · Boston, MA ·
- Work mode
- Hybrid
- Seniority
- Senior
- Employment
- Full time
- Category
- Project management
- Experience
- 4+ years
whoop · Boston, MA ·
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
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 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 $150,000 - $215,000. 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.