About The Role

The Role

We are building an edge AI system that monitors intersection safety in real time. We are expanding our detection capabilities and need a detail-oriented annotator to help us grow and maintain the training dataset that powers our models.

Responsibilities

You will annotate video clips of intersections using CVAT, our annotation platform. The majority of your work involves reviewing and correcting AI-generated pre-labels rather than drawing from scratch — you are the quality layer, not the production layer. Day-to-day tasks include reviewing auto-generated bounding boxes across object classes (pedestrians, vehicles, and others), applying tracking corrections when objects are occluded or conditions change, and flagging edge cases for engineer review.

Requirements

You have prior experience with CVAT, specifically with object tracking and interpolation workflows. You are comfortable working with video data across varied lighting and weather conditions. You have a high tolerance for repetitive, detail-oriented work and take quality seriously. Experience with YOLO-format datasets or prior computer vision annotation work is a strong plus.

Technology

Locations

Remote - LatAm
Remote status

Fully Remote

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TECHNOLOGY · REMOTE - LATAM · FULLY REMOTE