People Platform Lead

The People Platform Lead owns the full journey of the company’s expert network, turning strangers into productive, well-paid contributors who produce the reinforcement learning training data behind frontier AI models. This is a hands-on operating role that blends staffing, product thinking, and genuine care for the contributor experience.

The successful candidate will improve the existing platform immediately while rebuilding it to support a 10x to 100x larger expert pool. The role partners closely with a Senior Recruiter and with engineers, and requires someone who can turn process bottlenecks into clear product requirements and, where engineering capacity is limited, ship improvements independently using AI tools and coding agents. This person is also the public face of the expert program.

KEY RESPONSIBILITIES
• Expert lifecycle ownership: Own and continuously improve every stage of the expert journey, including the application site, interview gates, onboarding (background checks, KYC, contracts), project placement, and training.
• Scale: Future-proof the platform to grow the expert pool 10x to 100x, including testing and rolling out AI interviewers and other automation.
• Product requirements: Convert operational bottlenecks into well-defined product requirements and ship fixes in partnership with engineers and AI coding agents such as Claude.
• Staffing plans: Work with the Senior Recruiter to plan staffing for incoming projects and ensure experts have the right evaluation materials before they start.
• Quality: Protect contributor quality at every stage of the funnel through clear standards, feedback loops, and well-designed gates.
• Contributor experience: Act as the face of the expert program, building an experience that helps contributors succeed and makes senior professionals feel valued.
• Community and events: Run events and programs that engage the expert community and strengthen retention.
• Tooling and data: Manage the people-platform tool stack, including the applicant tracking system, and use data to identify drop-off, delays, and capacity gaps.