RLHF/AI Evaluation & Data Labeling Specialist
Applied structured analytical frameworks for the evaluation of multi-dimensional outputs in financial and operational data labeling scenarios. Conducted RLHF evaluation, preference ranking, and quality rating of responses, ensuring rigorous factual accuracy and consistency. Executed domain-expert labeling in finance, compliance, and institutional governance by systematically applying rubrics and annotation protocols. • Evaluated response quality, tone, style, and coherence in complex text outputs. • Identified edge cases and inconsistencies through multi-step logic and reasoning assessments. • Applied structured annotation and ensured inter-rater consistency across labeled datasets. • Used preference ranking and detailed reporting to inform AI and institutional feedback cycles.