Computer Vision Annotator (Remote)

About the role

We are looking for a detail‑oriented Computer Vision Annotator to work remotely worldwide. In this role you will create high‑quality labeled datasets that power computer‑vision and machine‑learning models across a variety of visual‑recognition tasks.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines and 3D cuboids on images, video and point‑cloud data using tools such as CVAT, Label Studio, 3D Slicer or Amazon SageMaker Ground Truth.
• Place key points for pose estimation and generate segmentation masks for semantic and instance segmentation.
• Interpret complex labeling taxonomies, resolve ambiguous cases and collaborate with project managers and data scientists to refine guidelines.
• Identify edge cases, potential biases and challenging patterns, and report findings to improve model robustness.
• Provide feedback on annotation tool performance and help develop best‑practice documentation and training material for new annotators.
• Assist with basic data‑preparation tasks such as image resizing, format conversion and sensor‑data synchronization.

Required profile

• Minimum two years of hands‑on experience in data annotation or quality assurance for computer‑vision or ML projects.
• Proven ability to maintain high accuracy and consistency across repetitive labeling tasks.
• Strong written and verbal communication skills in English.

Required skills

• CVAT, Label Studio, 3D Slicer, Supervisely, Amazon SageMaker Ground Truth.
• Bounding‑box, polygon, key‑point, 3D‑cuboid and segmentation‑mask annotation techniques.
• Point‑cloud and LiDAR data annotation.
• Knowledge of computer‑vision concepts such as object detection, image classification and tracking.
• Quality‑control methods including consensus labeling, audit sampling and inter‑annotator agreement metrics.