3D
data annotation
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I have five years of hands-on experience in data labeling and AI training, supporting the development, evaluation, and improvement of large-scale machine learning models. My work spans text, image, audio, and video annotation, including NLP tasks such as entity recognition, sentiment analysis, intent classification, and prompt–response evaluation, as well as computer vision tasks like bounding boxes, polygons, and segmentation. I consistently apply complex annotation and safety guidelines with a strong focus on accuracy, quality, and compliance, maintaining 95%+ quality scores across projects. What sets me apart is my ability to combine technical precision with critical reasoning. Beyond annotation, I perform quality review, error analysis, and model output evaluation, identifying patterns that help improve model performance, reliability, and safety. I am experienced in remote, high-volume AI workflows, trusted with sensitive datasets, and known for attention to detail, consistency, and strong instruction-following skills—qualities essential for high-impact AI training and evaluation work
data annotation
Master of Science, Computer Science
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