Teams at hud

Develop datasets, evaluation methods, validation tools, and quality standards for robotics and embodied AI systems. Translate research needs into dataset specifications, design collection protocols, audit multimodal robotics data, and run experiments analyzing how data quality and structure affect model performance. Collaborate with research, engineering, data providers, and customers to improve robotics data offerings.

Own customer-facing operations across data suppliers and AI labs, including activation, engagement, onboarding, contract and platform issue resolution. Build trust through customer conversations, coordinate internal blockers, and convert recurring feedback into improved processes, platform capabilities, communications, and lightweight workflow systems. The role requires strong judgment, organization, follow-through, CRM familiarity, and comfort working independently in a fast-paced startup environment.

Build full-stack tools, backend services, APIs, dashboards, and data workflows for assessing and improving AI training data and evaluations. Partner with quality and research teams to inspect agent trajectories, validate graders, measure quality, investigate workflow issues, and turn internal prototypes into reliable production platform capabilities.