AI Response Evaluator (Practice Project)
Reviewed AI-generated outputs and evaluated them for compliance with detailed guidelines. Applied RLHF-style rubrics to rate the quality, accuracy, and appropriateness of AI model responses. Identified and documented AI output errors, including hallucinations and incomplete results. • Consistently maintained accuracy above 98% through structured annotation workflows. • Collaborated remotely, ensuring adherence to quality standards and prompt resolution of errors. • Used SQL, Python, and Excel to verify outputs and document findings. • Provided improvement recommendations to support AI system enhancement.