Computer Vision Annotator

About the role

The Computer Vision Annotator will create high-quality labeled datasets that power computer-vision and machine-learning models. Working remotely, you will collaborate with data scientists and engineers to ensure precise annotation of images, videos and 3D sensor data.

Key responsibilities

• Draw accurate bounding boxes, polygons, polylines and 3D cuboids on visual data using tools such as CVAT, Label Studio, 3D Slicer or SageMaker Ground Truth.
• Place key points for pose estimation and perform semantic/instance segmentation to label every pixel.
• Annotate point-cloud and LiDAR data for autonomous-vehicle and robotics applications.
• Interpret detailed labeling taxonomies, resolve ambiguous cases and refine guidelines with project managers.
• Provide feedback on annotation tools, suggest workflow improvements and flag edge-case patterns that could bias models.
• 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.
• Strong understanding of computer-vision terminology (object detection, image classification, LiDAR, point clouds).
• Excellent attention to detail and ability to maintain consistency across large volumes of repetitive tasks.
• Fluent written and spoken English with clear documentation skills.

Required skills

• Proficiency with annotation platforms: CVAT, Label Studio, 3D Slicer, Supervisely, Amazon SageMaker Ground Truth.
• Experience creating bounding boxes, polygons, key-point sets, 3D cuboids and segmentation masks.
• Knowledge of quality-control methods such as consensus labeling, audit sampling, gold-task seeding and inter-annotator agreement metrics.