Computer Vision Annotator – Remote (Worldwide)

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

• Draw accurate bounding boxes, polygons, polylines and 3D cuboids around objects in images, video frames and point‑cloud data.
• Place key points for pose estimation and create semantic/instance segmentation masks.
• Interpret detailed labeling taxonomies and collaborate with data scientists to refine guidelines.
• Use annotation platforms such as CVAT, Label Studio, 3D Slicer, Supervisely or Amazon SageMaker Ground Truth.
• Identify ambiguous cases, edge‑cases and potential bias, escalating findings to improve model robustness.
• Provide feedback on tool performance and help develop best‑practice documentation for new annotators.
• Assist with basic data preparation tasks like image resizing, format conversion and sensor data synchronization.
• Track key performance indicators such as throughput, precision and recall.

Required profile

• Minimum two years of hands‑on experience in data annotation or quality assurance for computer‑vision projects.
• Strong attention to detail and a commitment to consistent, high‑accuracy output.
• Excellent written and verbal communication in English.
• Ability to work independently in a fully remote environment and collaborate with global teams.

Required skills

• Proficiency with CVAT, Label Studio, 3D Slicer, Supervisely or Amazon SageMaker Ground Truth.
• Experience creating bounding boxes, polygons, key points, 3D cuboids and segmentation masks.
• Familiarity with LiDAR and point‑cloud annotation.
• Understanding of computer‑vision concepts such as object detection, image classification and tracking.
• Knowledge of quality‑control processes like consensus labeling and inter‑annotator agreement.