Wizzi Junior

I’m a detail-oriented QA Analyst and AI Data Annotation Specialist with a background in Machine Learning. I focus on evaluating AI-generated content, validating datasets, and enforcing quality standards across text and image tasks. I’m driven by the idea that better feedback turns directly into better model performance.

Since 2024, as a QA Analyst / AI Data Quality Specialist (Freelance, Remote), I performed quality assurance on AI-generated content to ensure accuracy and consistency. I identified errors, improved data quality across model outputs, and conducted annotation and validation on text and image datasets. I also evaluated image generation results and prompt alignment, then delivered structured, actionable feedback reports for model improvement.

My QA approach combines data validation, bug reporting, and root cause analysis to spot inconsistencies early and keep outputs reliable. I apply AI annotation practices—including RLHF and AI output evaluation—and I support work across NLP, computer vision, and machine learning workflows. I’m currently building deeper technical strength through my Bachelor of Science in Machine Learning at Drexel University, and I work efficiently with tools like Google Sheets, Excel, Jira, and Notion.