Computer Vision Annotator

About the role

The Computer Vision Annotator will create high-quality labeled datasets for image and video streams, enabling the training of robust computer-vision and machine-learning models. Working remotely, you will collaborate with data scientists and engineers to ensure annotation consistency and accuracy across diverse projects such as object detection, segmentation, and 3D perception.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines and key-point annotations on images and video frames.
• Generate 3D cuboids and label point-cloud data for LiDAR-based applications.
• Perform semantic and instance segmentation, labeling every pixel where required.
• Interpret detailed labeling taxonomies and resolve ambiguous cases with project leads.
• Use annotation platforms such as CVAT, Label Studio, 3D Slicer, Supervisely or Amazon SageMaker Ground Truth.
• Provide feedback on tool usability and suggest workflow improvements.
• Identify edge cases, potential biases and report findings to enhance model robustness.
• Assist with basic data preparation tasks, including image resizing and format conversion.

Required profile

• Minimum 2 years of hands-on experience in computer-vision data annotation or quality assurance.
• Strong attention to detail and ability to maintain high accuracy on repetitive tasks.
• Excellent written and verbal communication in English.
• Proven ability to follow and document annotation guidelines.

Required skills

• Proficiency with CVAT, Label Studio, 3D Slicer, Supervisely, or Amazon SageMaker Ground Truth.
• Experience with bounding-box, polygon, key-point, 3D cuboid and segmentation mask annotation techniques.
• Understanding of computer-vision concepts such as object detection, image classification, and point-cloud processing.