Product Manager, Marketplace
About the role
HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25.
We’re looking a Product Manager to own product work for our data marketplace. You’ll make it easier for data vendors to bring high-quality RL environments and training data to HUD, and for research teams to discover, evaluate, and use them. You’ll work closely with engineering, research, and GTM to turn technical and operational needs into product decisions.
Team Size : ~25 people currently, mostly full-time in-person, but some remote. Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc. Company stage: We have 8 figures in funding and are scaling profitably and quickly to meet very strong demand.
Responsibilities
- Own the marketplace product lifecycle, from understanding vendor and buyer needs through prioritization, launch, and iteration
- Improve how vendors onboard, submit work, understand quality feedback, and manage their offerings on HUD
- Improve how research teams discover, assess, and access environments and training data that meet their needs
- Work with engineering, research, GTM, and operations to turn complex requirements and manual processes into reliable platform workflows
- Define and track measures of marketplace health, product adoption, and user experience; use feedback and product data to decide what to build next
Qualifications
- Experience owning a live software product from discovery through launch and iteration
- Strong product judgment and the ability to simplify technically complex workflows for users
- Experience talking directly with users, identifying the problem behind a request, and turning what you learn into clear priorities
- Ability to balance user needs, business impact, and engineering constraints when making product decisions
- Comfort using qualitative feedback and quantitative signals to assess whether a product change worked
- Clear written communication and the ability to bring