Remote Computer Vision Annotator

About the role

The Computer Vision Annotator will create high-quality labeled datasets for image and video streams, enabling the development of robust computer-vision and machine-learning models. Working remotely, you will collaborate with data scientists and engineers to ensure annotation accuracy across a variety of visual tasks.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines and 3‑D cuboids around objects of interest.
• Place key points for pose estimation and generate segmentation masks for pixel‑level labeling.
• Annotate point‑cloud and LiDAR data to support spatial‑awareness applications.
• Interpret complex labeling taxonomies and refine guidelines with project managers.
• Use annotation platforms such as CVAT, Label Studio, 3D Slicer or Amazon SageMaker Ground Truth.
• Identify ambiguous cases, edge‑cases and potential bias, and report findings to improve model robustness.
• Provide feedback on tool functionality and help optimise annotation workflows.
• Assist with basic data preparation tasks, including image resizing and format conversion.
• Track key performance indicators such as throughput, precision and recall.

Required profile

• Minimum 2 years of experience in data annotation or quality assurance for computer‑vision projects.
• Strong attention to detail and commitment to consistent, accurate labeling.
• Excellent written and verbal communication in English.
• Ability to document workflows clearly and collaborate with cross‑functional teams.

Required skills

• Proficiency with CVAT, Label Studio, 3D Slicer and Supervisely.
• Experience with bounding‑box, polygon, key‑point, 3‑D cuboid and segmentation‑mask annotation techniques.
• Solid understanding of computer‑vision concepts such as object detection, image classification and point‑cloud processing.
• Familiarity with quality‑control methods like consensus labeling and inter‑annotator agreement metrics.