Remote Computer Vision Annotator (Worldwide)

About the role

The Computer Vision Annotator will work remotely to label and annotate image and video datasets that train machine‑learning models. High‑quality annotations are essential for tasks such as object detection, segmentation, pose estimation, and 3D perception.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines, key points, 3D cuboids and segmentation masks using tools such as CVAT, Label Studio, 3D Slicer or Amazon SageMaker Ground Truth.
• Interpret complex labeling taxonomies, resolve ambiguous cases, and refine guidelines together with data scientists.
• Identify edge cases, bias patterns and data quality issues, and report findings to improve model robustness.
• Contribute to best‑practice documentation, workflow optimisation and training material for new annotators.
• Assist with basic data preparation tasks like 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 data annotation or quality assurance for computer‑vision or ML projects.
• Exceptional attention to detail and commitment to consistency across large volumes of data.
• Strong written and verbal communication skills in English.
• Ability to work independently in a fully remote environment.

Required skills

• Proficiency with annotation platforms: CVAT, Label Studio, 3D Slicer, Supervisely, Amazon SageMaker Ground Truth.
• Hands‑on experience with bounding‑box, polygon, key‑point, 3D cuboid and segmentation‑mask techniques.
• Understanding of computer‑vision concepts (object detection, image classification, LiDAR, point clouds).
• Familiarity with quality‑control methods such as consensus labeling, audit sampling and inter‑annotator agreement metrics.