Computer Vision Annotator – Remote (Worldwide)

About the role

The Computer Vision Annotator will work remotely to label and annotate image and video datasets that train machine‑learning models. You will ensure high‑quality annotations for tasks such as object detection, segmentation, pose estimation and 3D point‑cloud labeling.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines and key‑points on visual data using annotation platforms.
• Create 3D cuboids and label point‑cloud data for autonomous‑vehicle and robotics applications.
• Perform semantic and instance segmentation, labeling every pixel where required.
• Interpret detailed labeling taxonomies and collaborate with project managers and data scientists to refine guidelines.
• Use advanced features of tools such as CVAT, Label Studio, 3D Slicer, Amazon SageMaker Ground Truth and Supervisely.
• Identify ambiguous cases, edge‑cases and potential bias, and report findings to improve model robustness.
• Assist with basic data preparation tasks like image resizing, format conversion and sensor‑data synchronization.
• Track annotation KPIs (throughput, precision, recall) and contribute to best‑practice documentation.

Required profile

• Minimum 2 years of hands‑on experience in computer‑vision data annotation or quality assurance.
• Proven ability to produce consistent, high‑accuracy labels across repetitive tasks.
• Strong written and verbal communication in English.
• Attention to detail and commitment to quality control processes.

Required skills

• Proficiency with CVAT, Label Studio, 3D Slicer, Supervisely and Amazon SageMaker Ground Truth.
• Familiarity with annotation techniques: bounding boxes, polygons, key‑points, 3D cuboids and segmentation masks.
• Understanding of computer‑vision concepts such as object detection, image classification and point‑cloud processing.