Computer Vision Annotator – Remote

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 annotations meet strict accuracy standards.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines and 3D cuboids on images, video and point‑cloud data.
• Place key points for pose estimation and generate segmentation masks for pixel‑level labeling.
• Interpret complex taxonomies, resolve ambiguous cases and refine annotation guidelines.
• Use advanced features of tools such as CVAT, Label Studio, 3D Slicer and Amazon SageMaker Ground Truth.
• Identify edge cases, bias patterns and provide feedback to improve model robustness.
• Assist with basic data preparation tasks, including resizing images and synchronising timestamps.
• Track KPI metrics like throughput, precision and recall, and contribute to best‑practice documentation.

Required profile

• Minimum 2 years of experience in data annotation or quality assurance for computer‑vision projects.
• Strong attention to detail and ability to maintain consistency across large volumes of data.
• Excellent written and verbal communication in English.
• Proven ability to work independently in a remote environment.

Required skills

• Hands‑on experience with CVAT, Label Studio, 3D Slicer, Supervisely or similar annotation platforms.
• Familiarity with Amazon SageMaker Ground Truth.
• Knowledge of bounding‑box, polygon, key‑point, 3D cuboid and segmentation‑mask techniques.
• Understanding of computer‑vision concepts such as object detection, image classification, LiDAR and point‑cloud processing.
• Experience with quality‑control methods like consensus labeling and inter‑annotator agreement metrics.