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Freelancer Overview
My background is in AI engineering and computer vision research, which has given me a strong understanding of the role that high-quality training data plays in model performance. During my masters research, I worked with large image datasets to study adversarial vulnerabilities in Vision Transformers, a process that required careful attention to data integrity, annotation consistency, and how labeling decisions directly impact model behavior. This research-driven exposure to training data quality gives me a solid foundation for data labeling work.