Computer Vision Annotator

About the role

We are looking for a Computer Vision Annotator to join our remote team and create high-quality labeled datasets that power computer-vision and machine-learning models. The role involves precise annotation of images and videos, ensuring consistency and accuracy across a variety of tasks such as object detection, segmentation and 3-D labeling.

Key responsibilities

• Apply bounding boxes, polygons, polylines, key points, 3-D cuboids and segmentation masks to visual data using annotation platforms.
• Interpret detailed labeling taxonomies and resolve ambiguous cases in collaboration with project managers and data scientists.
• Use advanced features of tools such as CVAT, Label Studio, 3D Slicer or Amazon SageMaker Ground Truth to improve workflow efficiency.
• Identify edge cases, potential biases and data quality issues, and report findings to engineering teams.
• Assist with basic data preparation tasks, including image resizing, format conversion and sensor data synchronization.
• Track annotation KPIs (throughput, precision, recall) and contribute to best-practice documentation and training materials.

Required profile

• At least 2 years of hands-on experience in data annotation for computer-vision or machine-learning projects.
• Strong attention to detail and a commitment to delivering accurate, consistent labels.
• Excellent written and verbal communication in English.

Required skills

• Proficiency with annotation tools: CVAT, Label Studio, 3D Slicer, Supervisely, Amazon SageMaker Ground Truth.
• Familiarity with computer-vision concepts such as object detection, image classification, LiDAR and point-cloud data.
• Experience with quality-control processes like consensus labeling and inter-annotator agreement metrics.