Software Engineer, Data Quality

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. This role owns quality assurance and audit for data, working closely with the researchers who consume it and the teams who create it.

• 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.