Data Annotation QA Lead - Calibration & Quality

Roboticsconnected; Iowa; In loco; USD 60.000 - 80.000; Tempo pieno

Descrizione del lavoro

Mind Robotics is seeking a QA Reviewer & Calibration Lead to ensure our data annotation pipeline maintains high throughput with top quality. You will lead calibration sessions, identify systematic labeling issues, and work with reviewers and partner teams to resolve edge cases.

You will monitor quality metrics, provide targeted training, and collaborate cross-functionally to keep the data flywheel moving smoothly in a fast-paced AI deployment environment.

Competenze

• 2-4 years of experience in quality assurance, data annotation QA, or data review in high-velocity tech or AI environments.
• Meticulous attention to detail and strong ability to resolve ambiguous data scenarios.
• Clear written and verbal communication; ability to explain labeling rules clearly.
• Data fluency with dashboards and basic reports to track accuracy metrics and trends.

Mansioni

• Lead weekly calibration sessions with internal reviewers and vendor partners to ensure consistent labeling.
• Identify and fix quality issues; perform root-cause analysis on labeling discrepancies and implement feedback loops.
• Update labeling guidelines, edge-case taxonomies, and SOPs as requirements evolve.
• Monitor quality metrics and inter-annotator agreement across dashboards to meet production targets.
• Provide direct feedback and targeted training to reviewers navigating complex guidelines or multi-sensor data edge cases.
• Collaborate with technical leads, operations, and annotation teams to resolve taxonomy questions quickly.

Conoscenze

Quality assurance

Data annotation

Data review

Edge cases

Strumenti

Dashboards

Spreadsheets

Descrizione del lavoro

Mind Robotics is seeking a QA Reviewer & Calibration Lead to ensure our data annotation pipeline maintains high throughput with top quality. You will lead calibration sessions, identify systematic labeling issues, and work with reviewers and partner teams to resolve edge cases.

You will monitor quality metrics, provide targeted training, and collaborate cross-functionally to keep the data flywheel moving smoothly in a fast-paced AI deployment environment.