You will collaborate with cross-functional teams to identify user friction and build end-to-end product features for reinforcement learning environments. This role involves owning product improvements from problem definition through implementation, launch, and iteration based on user feedback.
Join a product engineering team building a platform and marketplace for reinforcement learning environments. You will combine product judgment, interaction design, and full-stack engineering to make complex workflows clearer for environment creators and AI research teams.
Work with product, design, engineering, research, and go-to-market partners to identify user friction and prioritize improvements.
Speak directly with users to understand challenges in creating, testing, evaluating, and discovering reinforcement learning environments.
Own product improvements from problem definition and prototyping through implementation, launch, and iteration.
Build frontend and backend features for onboarding, environment submission, review, and discovery workflows.
Design interfaces that help users understand agent runs, evaluation results, reward signals, and quality feedback.
Use user feedback and product data to refine experiences and inform tradeoffs.
Experience shipping software products end-to-end, from understanding user needs through implementation and iteration.
A technical degree and full-stack web application experience, including polished frontend interfaces and backend services or APIs.
Experience interviewing users and using qualitative feedback and product data to improve shipped products.
Strong interaction design and product judgment, especially for complex technical workflows and making decisions with incomplete information.
Background in developer tools, data-rich products, marketplaces, or products serving distinct user groups.
Familiarity with AI agents, evaluations, reinforcement learning, training data, or workflows involving review, debugging, and quality feedback.
Base salary range: $100,000 to $225,000 annually. Visa sponsorship is available.
Remote candidates are welcome, with 70% to 80% time zone overlap required with San Francisco or Singapore. Office locations are available in San Francisco and Singapore.
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