Senior Product Manager, AI

At the company, we're on a mission to unlock human performance and healthspan. the company empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. The AI team at the company turns continuous physiological data into recommendations members act on every day. The quality of that intelligence is the product, and as it reaches more members across more surfaces, the work of measuring it, choosing the models behind it, understanding what it costs, and giving the rest of the company the tooling to build on it has grown into a role of its own. the company 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 the company 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. RESPONSIBILITIES 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 the company building with AI has a fast, well-instrumented path from idea to shipped. Track the unit economics of AI at the company, 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. QUALIFICATIONS Depth in evaluation and measurement: you have defined how something gets measured, not only reported on it. 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. Experience with platform or internal-facing products, where the users are other teams. Technical fluency sufficient to partner with research and engineering as a peer, and to translate model behavior into member experience. A track record of driving cross-team programs with many dependencies and no direct authority. 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. Nice to have: internal AI tooling or evaluation frameworks; experience partnering with a research organization; wearables or sensor data; SQL or light scripting. 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. This role is based in the the company office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. the company is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility At the company, 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 the company and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $155,000 - $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. #J-18808-Ljbffr United States Digital Space LLC