Computer Vision Annotator (Remote)

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 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 of interest.
• Place key points for pose estimation and create pixel‑level segmentation masks.
• Annotate point‑cloud and LiDAR data for autonomous‑vehicle and robotics applications.
• Interpret complex labeling taxonomies and refine guidelines in collaboration with data scientists.
• Use advanced features of annotation platforms such as CVAT, Label Studio, 3D Slicer or Amazon SageMaker Ground Truth.
• Identify ambiguous cases, edge‑cases and potential dataset biases, and report them to improve model robustness.
• Contribute to best‑practice documentation, workflow optimisation and training material for new annotators.
• Assist with basic data preparation tasks like image resizing, format conversion and sensor data synchronization.

Required profile

• Minimum 2 years of hands‑on experience in visual data annotation or quality assurance for computer‑vision projects.
• Strong attention to detail and a commitment to consistent, high‑precision output.
• Excellent written and verbal communication skills in English.
• Ability to work independently in a fully remote environment.

Required skills

• Proficiency with annotation tools such as CVAT, Label Studio, 3D Slicer, Supervisely or Amazon SageMaker Ground Truth.
• Familiarity with computer‑vision concepts (object detection, segmentation, point‑cloud processing).
• Experience applying quality‑control methods like consensus labeling and inter‑annotator agreement metrics.