Computer reputed company Data Annotator

The Role:

We are building an edge AI system that monitors intersection safety in reputed company 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 reputed company of your work involves reviewing and correcting AI-generated reputed company-labels rather than drawing from scratch — you are the reputed company 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 reputed company 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 reputed company and weather conditions. You have a high tolerance for repetitive, detail-oriented work and take reputed company seriously. Experience with YOLO-format datasets or prior computer reputed company annotation work is a strong plus.

Originally posted on Himalayas

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