SNS College of Technology
B.E, Aerospace Engineering
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I have experience working with AI training data and data annotation projects involving text classification, content evaluation, data validation, and quality assurance. My work has focused on reviewing datasets for accuracy, consistency, and compliance with project guidelines, while maintaining high attention to detail and productivity standards. I am comfortable interpreting complex annotation instructions, identifying edge cases, and applying consistent labeling decisions across large volumes of data. Additionally, I have experience using digital tools and spreadsheets to track progress, perform quality checks, and ensure reliable dataset outputs. What sets me apart is my strong analytical thinking, ability to learn new guidelines quickly, and commitment to delivering high-quality results. I have a solid understanding of how training data impacts machine learning and AI model performance, which helps me approach annotation tasks with precision and context awareness. My combination of accuracy, problem-solving skills, and adaptability enables me to contribute effectively to AI training, data labeling, content review, and data quality improvement projects.
B.E, Aerospace Engineering
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