Remote Computer Vision Annotator – Data Labeling Expert

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 annotation accuracy across image, video, and 3D sensor data.

Key responsibilities

• Draw precise bounding boxes, polygons, polylines, key points, and 3D cuboids on visual data.
• Perform semantic and instance segmentation to label every pixel.
• Annotate point‑cloud and LiDAR data for autonomous‑vehicle and robotics projects.
• Interpret complex labeling taxonomies and refine guidelines with project managers.
• Use advanced features of CVAT, Label Studio, 3D Slicer, or Amazon SageMaker Ground Truth.
• Identify ambiguous cases, edge‑cases, and potential dataset biases, and report findings.
• Contribute to best‑practice documentation, workflow optimisations, and training materials.
• Assist with basic data preparation tasks such as resizing images and synchronising timestamps.

Required profile

• Minimum 2 years of experience in data annotation, labeling, or QA for computer‑vision or ML projects.
• Proven proficiency with a range of annotation techniques (bounding boxes, polygons, key points, 3D cuboids, segmentation masks).
• Strong understanding of computer‑vision concepts (object detection, image classification, LiDAR, point clouds).
• Familiarity with quality‑control processes such as consensus labeling and inter‑annotator agreement.
• Exceptional attention to detail and ability to maintain high accuracy on repetitive tasks.
• Excellent written and verbal communication in English.

Required skills

• CVAT
• Label Studio
• 3D Slicer
• Amazon SageMaker Ground Truth
• Supervisely

What we offer

• Fully remote work with flexible hours.
• Opportunity to contribute to cutting‑edge AI projects.
• Collaborative international team environment.