Data Operations QA & Audit (AI/Robotics)

Location: San Francisco, United States; on-site

Company

Develops general-purpose AI and learning algorithms for controlling robots across a wide range of tasks.

What you will do

• Own end-to-end QA and audit processes for multimodal data from third-party vendors and partners.
• Define sampling strategies, review workflows, pass/fail decisions, and audit trails before data reaches model training.
• Translate research needs into measurable data-quality rubrics and acceptance criteria, keeping them versioned as requirements evolve.
• Build software interfaces, tooling, and infrastructure for automated sampling, internal checks, and vendor-quality monitoring.
• Provide structured feedback to vendors, help establish their own QA checks, and enforce standards through review and acceptance processes.

Requirements

• Approximately 5 years of experience building customer-facing software.
• Experience managing vendors and improving the quality of third-party data outputs through actionable feedback.
• Strong operations skills with a focus on instrumentation, measurement, and rapid iteration.
• Hands-on experience reviewing data samples, writing rubrics, and spot-checking program outputs.
• Clear written and verbal communication with researchers, operations teams, and external partners.
• Ability to work on-site in San Francisco.

Nice to have

• Experience with robotics, egocentric video, or other multimodal sensor data.
• Experience defining requirements for QA or validation tooling and collaborating with engineers on automated data-quality checks.

Culture & Benefits

• Work alongside engineers, scientists, roboticists, researchers, operations teams, and external data partners.
• Contribute to the development of robot foundation models and general-purpose physical-world AI.