About the Role Join a product engineering team building a platform and marketplace for reinforcement learning environments. You will own end-to-end product challenges that help creators submit and discover work, and help research teams evaluate and improve AI agents. What You'll Do • Partner with product, design, engineering, research, and go-to-market teams to identify user friction and prioritize improvements. • Speak directly with environment creators and research teams about creating, testing, evaluating, and discovering reinforcement learning environments. • Design, prototype, and ship improvements across the platform and marketplace, from problem definition through launch and iteration. • Build frontend and backend features for onboarding, submissions, review, and discovery workflows. • Make agent runs, evaluation results, reward signals, and quality feedback easier to understand and act on. • Use user feedback and product data to assess outcomes, refine experiences, and inform tradeoffs. What We're Looking For • Experience shipping software products end-to-end, from understanding user needs through implementation and iteration. • Full-stack web application experience, including polished frontend interfaces and backend services or APIs. • Strong product judgment, including identifying underlying problems, setting scope, and making tradeoffs with incomplete information. • Experience interviewing users and applying qualitative feedback and product data to improve shipped products. • Interaction design skills and a focus on clarity and usability in complex technical workflows. • 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 for review, debugging, and quality feedback. • Clear communication and experience working across cross-functional teams. Compensation & Benefits Base salary range: $100,000 to $225,000 USD annually. Visa sponsorship is available. Location Remote, with 70% to 80% time zone overlap with San Francisco, California or Singapore. The role is also associated with offices in San Francisco and Singapore.