Scene Understanding Labeler

We need annotators who can mark visual data accurately and efficiently. You will work through image queues, applying labels, bounding boxes, keypoints, or segmentation masks according to project-specific guidelines. Some tasks involve single-frame annotation; others require tracking objects across video sequences. Attention to spatial detail is critical -- the difference between a good and bad annotation is often just a few pixels.

Prior experience with annotation tools like CVAT, Labelbox, V7, or Supervisely is preferred but not required -- our platform is intuitive and we train you during onboarding. What we cannot teach is visual acuity and spatial precision. You should have a good eye for detail and the patience to outline objects carefully rather than rushing through tasks. Familiarity with basic computer vision concepts (object detection, segmentation, keypoints) is a plus.

Projects run in weekly sprints with clear volume targets. You will know at the start of each week how many images or frames to annotate. Most annotators work 15-25 hours per week. A brief weekly call with the project lead covers guideline updates and quality feedback.