Teams at Build AI

Build internal software for field collection operations, including tasking, site setup, device inventory, shift tracking, local tools, and site-health monitoring. Improve operational efficiency by observing field workflows, removing bottlenecks, and making site expansion repeatable. Integrate field tools with data infrastructure and marketplace incentives, while collaborating closely with on-the-ground teams and occasionally traveling to field sites.

Owns dataset strategy and quality for physical labor AI data. Defines the ideal dataset, objective functions, taxonomy, golden sets, acceptance criteria, audits, and incremental data value. Converts these frameworks into collection strategies, operational standards, and vendor requirements while optimizing information gain over unnecessary fidelity or volume. Partners with marketplace, software, research, and evaluation teams to connect dataset quality with model capability.

Build and ship a visualization product for datasets, collection, quality, evaluations, and live pipeline health. Responsibilities include developing web or CLI interfaces, enabling fast exploration of video, pose, batches, coverage, failures, and statistical summaries, and partnering with research and operations teams. The role emphasizes performance, shareability, high-volume media, and production-quality internal tools in a zero-to-one environment.