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Senior Product Manager (Artificial Intelligence)

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Onsite

Senior Product Manager (Artificial Intelligence)

WHOOP

Senior Product Manager (Artificial Intelligence)

Skills

SQL QueriesMachine LearningAIProduct Manager

2 months ago

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Important information


Contract type:

Permanent

Salary:

$155,000 – $215,000 / year

Location:

Boston, MA, USA

Work mode:

Onsite

Published on:

11 September 2026

What they need


  • WHOOP is hiring a Senior Product Manager to work at that layer, alongside our AI engineers, research scientists, and data scientists. The work spans how AI output quality gets measured and enforced, which models and providers power which experiences, the internal AI platform that teams across WHOOP use to build agents, and which emerging techniques from the research world are worth a bet
  • This is a platform-oriented AI product role. Your users are as often internal (agent authors, analysts, engineers, research scientists) as they are members. It suits someone technical enough to earn the trust of ML researchers, organized enough to run a program across several teams without direct authority, and disciplined enough to say no to most of what is possible
  • Shape how AI output quality is measured across WHOOP’s AI experiences, including the evaluation methodology, datasets, and scoring that make quality continuous and trusted rather than judged case by case
  • Build the evaluation habit across the company: make evals self-serve, and get the teams shipping AI features to actually run them
  • Help decide which models power which experiences, and which providers we run them on, balancing quality, latency, and cost as the model landscape shifts
  • Product-manage our internal AI development platform and drive its adoption, so that anyone at WHOOP building with AI has a fast, well-instrumented path from idea to shipped
  • Track the unit economics of AI at WHOOP, including cost per interaction, and drive the tradeoffs between quality, latency, and spend
  • Explore where AI capability goes next, from fine-tuning and reinforcement learning to distillation and emerging foundation models, and turn a broad field of options into a small number of well-scoped bets, starting with internal productivity

Benefits

  • Flexible Vacation: WHOOP has a flexible vacation policy that allows you to unwind, laptop-free, when you need it most.
  • Focus on Family: We offer 18 weeks paid parental leave, plus an additional 2 weeks to gradually return to work.
  • Get Invested: In addition to a competitive base salary and 401k, you’re eligible to receive stock options to share in the future of WHOOP.
  • WHOOP +1: Everyone on the team gets a complimentary WHOOP membership—plus another membership to share with a loved one.
  • Health Matters: Our competitive benefits package covers medical, dental, and vision, in addition to mental health services, life and disability insurance, and more.
  • Find Your Fit: Full-time employees get $500 a year to spend on wellness in whatever way they see fit, from fitness classes and memberships, to recovery services.
  • It Pays to Sleep: Our Sleep Performance Program incentivizes employees to get more sleep. Log an average sleep performance of 85% or higher for the month and get a $100 bonus.
  • Location, Location, Location: You can’t beat the views from the rooftop of One Kenmore Square. Feel inspired daily as you work, enjoy free snacks and coffee, and collaborate in the heart of Boston.- Experience with platform or internal-facing products, where the users are other teams
  • Nice to have: internal AI tooling or evaluation frameworks; experience partnering with a research organization; wearables or sensor data; SQL or light scripting
  • Working literacy in modern ML: you understand what fine-tuning is and the main flavors of it, what RL-based post-training is for, and how the current generation of techniques fits together. You do not need to implement them, but you should know what they buy you and what they cost
  • Depth in evaluation and measurement: you have defined how something gets measured, not only reported on it
  • Sound business judgment: you can quantify a tradeoff, reason about cost, and decline work that will not pay for itself
  • Comfort operating in ambiguity, with evidence of turning a broad set of possibilities into one well-scoped bet
  • Technical fluency sufficient to partner with research and engineering as a peer, and to translate model behavior into member experience
  • Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions
  • Experience shipping AI or machine learning products, where the underlying capability was probabilistic rather than deterministic
  • A track record of driving cross-team programs with many dependencies and no direct authority
  • Interested in the role, but don’t meet every qualification? We encourage you to still apply!

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