AI Trainer & Data Reviewer (Outlier AI)
Reviewed and evaluated AI-generated responses for accuracy, reasoning quality, instruction following, tone, and factual consistency. Applied detailed scoring rubrics for ranking, edge-case analysis, prompt evaluation, and QA review workflows. Identified systematic issues and inconsistencies in model outputs to improve data quality and training outcomes. • Accuracy, reasoning quality, and instruction-following evaluation • Prompt and response scoring using rubrics for ranking workflows • Edge-case analysis and quality assurance review • Detection of inconsistencies to improve training data quality