Computer Vision QA Specialist

In this hourly, remote contractor role, you will work as a Computer Vision QA Specialist to review image and video annotations for quality, accuracy, and guideline compliance. You will evaluate annotations such as bounding boxes, segmentation masks, polygons, keypoints, object classes, attributes, and video tracks, identifying missing, incorrect, inconsistent, or poorly placed annotations.

You will also make corrections when required, provide clear feedback on quality issues, and communicate unclear cases to the project team. This role requires strong attention to detail, consistency, and the ability to carefully follow detailed computer vision annotation guidelines.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your computer vision QA work directly helps improve the world’s premier AI models by ensuring that visual training data is accurate, complete, consistent, and aligned with project expectations.

What you'll do

• Review annotation quality: Review image and video annotations for accuracy, completeness, consistency, and adherence to project guidelines.
• Check annotation outputs: Evaluate bounding boxes, classes, attributes, segmentation masks, polygons, keypoints, image labels, and video tracking outputs.
• Identify annotation errors: Spot missing objects, incorrect labels, inaccurate boundaries, poor box placement, inconsistent attributes, duplicate annotations, and unclear edge cases.
• Make corrections when required: Correct annotation issues according to project-specific instructions and quality standards.
• Provide clear feedback: Document quality issues clearly so annotators or project teams can understand what needs to be improved.
• Follow project guidelines: Apply detailed annotation rules consistently across tasks, including rules for occlusion, truncation, blur, small objects, overlapping objects, and ambiguous cases.
• Escalate unclear cases: Communicate questions or uncertain examples to the project team for clarification.
• Maintain consistent work quality: Complete assigned QA work reliably while maintaining accuracy, consistency, and expected productivity.

What we're looking for

• Previous experience with computer vision annotation, image annotation, video annotation, or annotation QA is preferred.
• Experience reviewing or creating annotations such as bounding boxes, polygons, segmentation masks, keypoints, object classes, attributes, image classification, or video object tracking.
• Strong attention to detail and ability to identify missing, incorrect, inconsistent, overlapping, mislabeled, or poorly placed annotations.
• Comfortable working with detailed annotation guidelines, edge-case rules, quality standards, and project-specific instructions.
• Ability to review image and video data consistently across large batches while maintaining accuracy and speed.
• Comfortable making corrections when required and explaining annotation errors clearly.
• Good professional proficiency in English to understand guidelines, communicate questions, and provide written feedback.
• Able to work independently in an hourly remote workflow and commit consistent working hours based on project needs.
• Prior experience with annotation platforms such as SuperAnnotate, Labelbox, CVAT, Scale, Appen, Remotasks, Toloka, or similar tools is preferred.