Remote Computer Vision Annotator – Data Labeling Specialist

About the role

The Computer Vision Annotator will work remotely to create high‑quality labeled datasets that power computer‑vision and machine‑learning models. You will annotate images and videos, ensuring precise bounding boxes, polygons, key points, 3D cuboids and segmentation masks that meet project specifications.

Key responsibilities

• Apply annotation tools (CVAT, Label Studio, 3D Slicer, Amazon SageMaker Ground Truth) to draw bounding boxes, polygons, polylines, key points and 3D cuboids.
• 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 risks and data patterns, escalating findings to improve model robustness.
• Contribute to best‑practice documentation, workflow optimisation and training of new annotators.
• Assist with basic data preparation such as image resizing, format conversion and sensor‑data synchronization.
• Track annotation KPIs (throughput, precision, recall) and participate in calibration sessions.

Required profile

• Minimum 2 years of experience in computer‑vision data annotation or quality assurance.
• Strong attention to detail and ability to maintain accuracy on repetitive tasks.
• Excellent written and verbal communication in English.

Required skills

• Proficiency with CVAT, Label Studio, 3D Slicer, Supervisely.
• Experience with bounding‑box, polygon, key‑point, 3D cuboid and segmentation‑mask annotation techniques.
• Understanding of computer‑vision concepts such as object detection, image classification, LiDAR and point‑cloud data.
• Familiarity with quality‑control methods like consensus labeling, audit sampling and inter‑annotator agreement metrics.