QA Reviewer, Data Annotation

Roboticsconnected; Iowa; On-site; USD 60,000 - 80,000; Full time

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Quality assurance

Data annotation

Data review

Edge cases

Tools

Dashboards

Spreadsheets

Job description

QA REVIEWER, DATA ANNOTATION

ABOUT MIND:

Mind Robotics is building Physical AI for real-world industrial deployment, starting with the factory floor. We believe the hardest problems in AI are solved when researchers and engineers are hands-on with the physical world every day - and we're looking for people who are passionate about robotics, value ownership, and are excited to tackle difficult problems. Join us if you want to move beyond digital intelligence and put intelligence into motion.

ABOUT THE TEAM AND THE ROLE:

We are looking for a QA Reviewer & Calibration Lead to ensure our data annotation pipeline operates at high throughput without sacrificing quality. In this role, you will be the backbone of quality control for our continuous data flywheel. You will lead regular alignment sessions, identify systematic labeling inconsistencies, and work hands-on with internal reviewers and partner teams to resolve ambiguous edge cases.

Responsibilities:

• Run calibration sessions: Lead weekly alignment meetings with internal reviewers and vendor partners to ensure everyone grades and labels data with high consistency.
• Track and fix quality issues: Spot common reviewer errors, conduct root-cause analysis on labeling discrepancies, and build feedback loops to eliminate systemic mistakes.
• Update guidelines and documentation: Keep labeling instructions, edge-case taxonomies, and SOPs clear, crisp, and up-to-date as project requirements evolve.
• Monitor quality metrics: Track quality scores, accuracy rates, and inter-annotator agreement metrics across dashboards to ensure production targets are met.
• Provide feedback and guidance: Deliver direct feedback and targeted training to reviewers navigating complex guidelines or multi-sensor data edge cases.
• Coordinate cross-functionally: Work closely with technical leads, operations, and annotation teams to resolve taxonomy questions quickly and keep the data flywheel moving smoothly.

REQUIREMENTS:

• 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: A sharp eye for subtle edge cases and a practical, logical approach to resolving ambiguous data scenarios.
• Clear communication: Strong written and verbal communication skills with the ability to explain complex labeling rules clearly and facilitate alignment discussions.
• Data fluency: Comfortable navigating dashboards, spreadsheets, and basic reports to track accuracy metrics and spot trends.
• Collaborative mindset: A proactive, team-oriented attitude focused on coaching reviewers and continually driving quality across the organization.
• Experience with multi-camera/ego-exo video annotation, point cloud data, or robotics training data pipelines (is a plus).
• Background working with third-party vendor teams (BPO/managed services) in a fast-paced hardware or AI deployment environment (is a plus).