Computer Vision Annotator

About the role

The Computer Vision Annotator works remotely to create high‑quality labeled datasets that power computer‑vision and machine‑learning models. You will use specialized annotation tools to mark images and videos, ensuring precision for tasks such as object detection, segmentation, and 3D perception.

Key responsibilities

• Draw accurate bounding boxes, polygons, polylines, and key points on visual data.
• Create 3D cuboids and annotate point‑cloud data for autonomous‑vehicle and robotics applications.
• Perform semantic and instance segmentation, labeling every pixel in an image.
• Interpret complex labeling taxonomies and refine guidelines with project managers and data scientists.
• Utilize tools like CVAT, Label Studio, 3D Slicer, and Amazon SageMaker Ground Truth.
• Identify ambiguous cases, edge cases, and potential biases, and report findings.
• Contribute to best‑practice documentation, workflow optimization, and training of new annotators.
• Assist with basic data preparation tasks such as resizing images and synchronizing sensor timestamps.

Required profile

• Minimum 2 years of experience in data annotation or quality assurance for computer‑vision projects.
• Strong attention to detail and commitment to accuracy.
• Excellent written and verbal communication in English.
• Ability to follow and document detailed annotation guidelines.

Required skills

• Proficiency with CVAT, Label Studio, 3D Slicer, Supervisely, or Amazon SageMaker Ground Truth.
• Experience with bounding boxes, polygons, key points, 3D cuboids, and segmentation masks.
• Knowledge of quality‑control methods such as consensus labeling, audit sampling, gold‑task seeding, and inter‑annotator agreement metrics.
• Understanding of computer‑vision concepts: object detection, image classification, LiDAR, point clouds.