Physical Intelligence

Physical Intelligence

Software Engineer, Data Quality

San Francisco

Sponsorship not specifiedDetected 52 days ago
AlgorithmsVendor ManagementRoboticsResearchCommunication

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Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • Physical Intelligence is bringing general-purpose AI into the physical world.
  • The Team Training robot foundation models takes enormous amounts of multimodal data.
  • The Data Operations team makes sure that data is high quality, well understood, and safe to train on.

Responsibilities

  • Own external data QA & audit: Build and run the end-to-end QA process for multimodal data ingested from third-party vendors and partners - sampling strategy, review workflows, pass/fail decisions, and audit trails - so data is verified before it reaches training.
  • Define quality standards: Partner with researchers to translate what "good data" means into concrete, measurable rubrics and acceptance criteria; keep them versioned and current as research needs evolve.
  • Build the system: Build the software interfaces, tooling, and infrastructure scale the system in an automated way - correctly sampling the right data for QA, internal QA checks, tracking dips in data quality from vendors and exposing those insights back to the vendors.
  • Manage vendor quality loops: Deliver structured, actionable feedback to vendors; coach them on standing up QA checks on their own side; iterate until vendor-side and internal QA agree; enforce standards through review and acceptance processes.
  • Strong ops acumen and drive - a bias to instrument, measure, and iterate quickly rather than crank hours at a broken process.
  • Comfort being hands-on in the data: reviewing samples yourself, writing and refining rubrics, and spot-checking your own program's output.
  • Clear written and verbal communication across researchers, operations teams, and external partners.

Requirements

  • ~5 years of experience across building customer facing software.

Nice to have

  • Experience with robotics, egocentric video, or other multimodal sensor data.
  • Experience defining requirements for QA/validation tooling or working with engineers on automated data quality checks.
  • Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Company info

  • Training robot foundation models takes enormous amounts of multimodal data.
  • This role owns quality assurance and audit for data, working closely with the researchers who consume it and the teams who create it.
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