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ImageI am a detail-oriented data annotation specialist and QA reviewer with hands-on experience labeling, evaluating, and documenting diverse AI training datasets using strict rubrics and taxonomies. My background includes identifying edge cases, maintaining labeling consistency, and producing structured feedback and reports for model improvement. I am skilled in Python, JavaScript, and TypeScript, and have built practical tools such as dataset QA checkers, annotation workflow trackers, and AI output evaluation dashboards. I am comfortable with remote, asynchronous work, and excel at clear written communication, guideline adherence, and reproducible reporting. My projects span text classification, safety tagging, and workflow automation, and I am committed to delivering high-quality, actionable data for AI development.
I used to train AI in that I would select pictures then I would crop people out of the picture and then I will write down instructions on how to obtain the initial image from the current image.
In this project, I used to correct the transcriptions made by AI, and I would also proof read that what was in the text is what the AI has transcribed.
Bachelor of Science, Data Science, Artificial Intelligence, and Computer Science
Associate Degree, Computer Science and Software Engineering
Software Engineering Portfolio Builder
