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ImageI am a systems engineering researcher with hands-on experience in machine learning and deep learning, particularly within the context of I am an experienced AI training data specialist with a strong background in text and image annotation, data validation, and quality assurance. I have worked on projects involving text classification, sentiment analysis, named entity recognition (NER), content moderation, and structured data labeling. I consistently follow complex annotation guidelines with high accuracy, ensuring strong inter-annotator agreement and reliable training datasets. My work supports the development and fine-tuning of machine learning models by delivering clean, well-structured, and precisely labeled data. What sets me apart is my attention to detail, speed without compromising quality, and ability to quickly adapt to new tools and evolving project requirements. I proactively identify inconsistencies in guidelines, provide constructive feedback, and maintain clear communication with team leads to improve overall dataset quality. I am comfortable working independently in remote environments, meeting tight deadlines, and handling large-scale labeling tasks efficiently. My goal is always to contribute to high-performing AI systems through accurate, scalable, and dependable data annotation.
Worked to refine generative AI models by examining the accuracy and relevance of their outputs. Created and addressed questions related to AI functionalities while evaluating the model’s performance to boost its precision.
Master of Science, Electronics and Communications Engineering
Bachelor of Science, Electronics and Computer Engineering
Test Engineer
Electronics Test Engineer
