AI Trainer, Outlier AI (AI training/tutoring via rubric-based evaluation)
Evaluated AI model outputs against structured quality rubrics to provide detailed feedback. Reviewed prompt-response datasets to identify edge-case errors and recurring patterns in model behavior. Delivered structured feedback reports to project leads to support iterative model refinements within defined review cycles. • Applied analytical judgment during systematic data review • Identified and documented quality issues affecting accuracy and consistency • Communicated findings in review-cycle reports • Supported measurable improvements through rubric-based assessment