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.

What you'll bring

~5 years of experience across building customer facing software.

Vendor management experience: working directly with third-party data providers, delivering actionable feedback, and measurably improving the quality of their output.

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.

Product Engineer

Responsibilities

Qualification

Required

Preferred

Company

Physicalintelligence

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