Data Quality Engineer: Multimodal Robotics & Vendor QA

Physical Intelligence; United States; On-site; USD 90,000 - 150,000; Full time

Job summary

Physical Intelligence is building general-purpose AI-enabled robotics software in San Francisco, bringing data-driven QA to training datasets. This role focuses on QA and audit of multimodal data from vendors to ensure quality before model training.

You will partner with researchers to define concrete, measurable quality rubrics, build the tooling to automate sampling and validation, and coach vendors to meet internal standards.

Qualifications

• ~5 years of experience across building customer facing software.
• Vendor management with third-party data providers.
• Strong ops acumen with data-driven decision making.
• Hands-on in data: reviewing samples, writing rubrics, and auditing outputs.
• Clear written and verbal communication with researchers, ops teams, and partners.

Responsibilities

• Own external data QA & audit: build end-to-end QA for data from vendors, with sampling, review workflows, pass/fail decisions, and audit trails.
• Define quality standards with researchers and translate them into measurable rubrics.
• Build software interfaces, tooling, and infrastructure to scale automated data QA and track data quality.
• Manage vendor quality loops: provide feedback to vendors and align QA standards between vendor and internal teams.

Skills

Vendor management

Ops analytics

Data QA

Hands-on data review

Communication skills

Software development

Job description

Physical Intelligence is building general-purpose AI-enabled robotics software in San Francisco, bringing data-driven QA to training datasets. This role focuses on QA and audit of multimodal data from vendors to ensure quality before model training.

You will partner with researchers to define concrete, measurable quality rubrics, build the tooling to automate sampling and validation, and coach vendors to meet internal standards.