Computer Vision Annotator

About the role

The Computer Vision Annotator works remotely to create high‑quality labeled datasets that power computer‑vision and machine‑learning models. You will handle image and video data, ensuring precise annotations that improve model accuracy across tasks such as object detection, segmentation, and 3‑D perception.

Key responsibilities

• Draw bounding boxes, polygons, polylines, key points, and 3‑D cuboids on visual data using tools like CVAT, Label Studio, 3D Slicer, or Amazon SageMaker Ground Truth.
• Perform semantic and instance segmentation, labeling every pixel where required.
• Interpret complex taxonomies, resolve ambiguous cases, and collaborate with data scientists to refine guidelines.
• Identify edge cases, bias patterns, and data quality issues, escalating findings to improve model robustness.
• Contribute to best‑practice documentation, workflow optimizations, and training materials for new annotators.
• Assist with basic data preparation tasks such as image resizing, format conversion, and sensor data synchronization.

Required profile

• Minimum 2 years of experience in data annotation or quality assurance for computer‑vision projects.
• Strong attention to detail and ability to maintain consistent, high‑precision output.
• Excellent written and verbal communication in English.

Required skills

• Proficiency with annotation platforms: CVAT, Label Studio, 3D Slicer, Supervisely, Amazon SageMaker Ground Truth.
• Hands‑on experience with bounding boxes, polygons, key points, 3‑D cuboids, and segmentation masks.
• Familiarity with computer‑vision concepts such as object detection, image classification, LiDAR, and point‑cloud data.
• Understanding of quality‑control methods like consensus labeling, audit sampling, and inter‑annotator agreement metrics.