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ImageI am an AI-focused data quality specialist with hands-on experience in large-scale data annotation, evaluation, and quality assurance for LLM training. My background includes auditing and calibrating diverse text and numerical datasets, applying strict guidelines to ensure consistency, and reviewing AI-generated outputs for accuracy and alignment. I am skilled in using Python, Excel, annotation platforms, and quality control pipelines to improve data reliability and downstream model performance. My work emphasizes data-centric AI practices, preference data evaluation (including RLHF/DPO concepts), and scalable QA workflows. I am passionate about advancing data quality to support cutting-edge AI research and development.
Worked as a Remote Data Contributor, supporting AI and machine learning projects through data annotation, labeling, and quality review while following strict guidelines to ensure accuracy and consistency
Bachelor of Arts, Information Studies
Research Participant
