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Build AI

Public-benefit data hyperscaler for physical AI

Head of Data Compliance

Privacy & Data ProtectionConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$160k - $250k /yr

About the Job

Requirements

  • Experience in privacy, employment or contractor compliance, or data-collection compliance within a real operating company rather than policy theory.
  • Ability to write compliance documents and ensure they are implemented in the field.
  • Willingness to work with in-the-wild physical labor collection and a company moving quickly across countries.

Responsibilities

  • Write and maintain consent, contractor and worker terms, privacy notices, retention documents, and cross-border transfer documents for in-the-wild collection.
  • Build privacy-by-design into collection workflows, including consent capture, data minimization, retention and deletion, and access controls.
  • Enable scaling by ensuring aggressive collection strategies are legally compliant, including in new countries and setups, before teams arrive.
  • Work with operations, marketplace, and software teams to integrate consent and legal compliance into product workflows.
  • Handle trade and cross-border issues for collection devices and data involving the United States, China, and new countries, including determining what can and cannot be transferred.
  • Ensure actual practices match the governing documents and close any gaps.

Desired Qualifications

  • Experience with cross-border data involving the United States, China, or new countries, and/or trade or export matters for hardware and datasets.
  • Employment or contractor law experience in physical workplaces.
  • Experience writing consent flows that operators actually used.
  • Familiarity with retention and deletion, data minimization, or privacy-by-design in a product.

About the Company

Build AI

Public-benefit data hyperscaler for physical AI

Build AI runs as a public benefit corporation that acts as a data hyperscaler for physical artificial intelligence, handling hardware, data collection, and model training in one end-to-end pipeline. It collects an egocentric dataset of physical labor by equipping thousands of workers with head-mounted cameras in real-world settings, then provides this data to researchers and corporate robotics teams to train physical AI models. The company differentiates itself by being vertically integrated—owning the hardware, data collection, and training process—and by focusing on large-scale, real-world data rather than relying on third-party sources. Its goal is to accelerate the development of robots that can perform manual tasks in everyday human environments, unlocking human potential.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2025

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