Amazon · amazon.jobs · checked today
Robotics Data Engineer, Frontier AI & Robotics (FAR)
Are you interested in solving the most critical operations problem behind cutting-edge robotics development? Interested in fast dynamic environment? Amazon's Frontier AI & Robotics (FAR) team is building advanced robotic systems through frontier foundation models, and high-quality data collection is a core input to that research.
Skills, with evidence
- Data quality
Working understanding of how collection quality, task coverage, and consistency affect model training and evaluation, with the ability to translate research requirements into executable procedures and quality checks.
must have - Machine learning
Experience supporting ML/AI data collection, annotation, quality assurance, or model evaluation workflows.
must have · not practised here - AWS
Experience diagnosing hardware, software, or process issues, using evidence to identify root causes and implement corrective actions.
not practised here - Failure handling
- Partner with researchers to develop and refine SOPs, translating task objectives, failure modes, and evaluation feedback into clear collection instructions and acceptance criteria.
Your plan
- The SQL screen: correct, then fast≈ 1 h
Data quality
- Average order value by countryFoundations
- Bucket missing countriesFoundations
- Customers who never orderedFoundations
- Hiring funnel by roleFoundations
- Orders with no line itemsFoundations
- Pipeline design: safe to run twice≈ 3 h
Failure handling
- After the first one finishesFoundations
- The history nobody keptFoundations
- The spreadsheet is a dependencyFoundations
- Waiting for the fileFoundations
- Where did the rows go?Foundations
- Say it out loud≈ 1 h
10 drills · Foundations + Intermediate≈ 4 hours
Not covered by the plan: Machine learning, AWS.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 4 dremoved the moment Amazon closes it