AI Trainer at Platform (2021–Present) — AI response evaluation and feedback for model improvement
Evaluated AI model responses for accuracy, relevance, and safety to support iterative improvements. Provided detailed feedback to guide refinement of model outputs and performance across varied scenarios. Tested edge cases to uncover failure modes and recommend targeted updates for training datasets. • Assessed response quality against predefined criteria (accuracy, relevance, safety) • Delivered structured feedback and improvement suggestions • Conducted edge-case testing and gap identification • Maintained documentation of findings and recommendations