AI training & data labeling / annotation work (2024–Present, as part of AI training specialization)
Evaluated AI-generated outputs for accuracy, consistency, and relevance as part of AI training workflows. Performed data annotation and quality assurance checks to support machine learning model development and improvement. Developed and tested prompts to identify issues and improve downstream model performance. • Assessed model outputs for correctness and relevance • Identified errors and edge cases using analytical review • Supported iterative prompt refinement cycles • Conducted labeling QA to maintain dataset quality