Image Annotation
Labeled vehicles, pedestrians, traffic lights, and road signs using bounding boxes. Applied occlusion notes and visibility attributes. Average task time: 20–35 seconds per image
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I have built over 3 years of experience contributing to high‑priority projects across leading platforms such as Scale AI, Remotasks, and TELUS International. My expertise spans multimodal dataset labeling, including bounding boxes, polygon segmentation, keypoint tagging, and metadata structuring, with QA accuracy consistently ranging between 92%–97%. Through this work, I have developed strong skills in guideline interpretation, error correction, and quality assurance, ensuring that datasets meet the highest standards of precision and consistency. I am proficient with industry‑standard tools like Labelbox, CVAT, Supervisely, and Amazon SageMaker Ground Truth, and hold contributor certifications in computer vision annotation, video tracking, and content moderation. My proven ability to deliver accurate results under tight deadlines makes me a reliable contributor for remote, project‑based AI training assignments.
Labeled vehicles, pedestrians, traffic lights, and road signs using bounding boxes. Applied occlusion notes and visibility attributes. Average task time: 20–35 seconds per image
Anvidelis M. hasn’t added any Education History to their OpenTrain profile yet.
Digital Operations Associate