Pawan Ruhil

Performed post-training evaluation and quality assessment of Large Language Model (LLM) outputs. Reviewed AI-generated responses for accuracy, relevance, factual correctness, and adherence to guidelines. Conducted data annotation, prompt testing, and response validation to improve model performance. Identified model errors, inconsistencies, and hallucinations, providing detailed feedback for refinement. Assisted in dataset preparation, quality control, and benchmarking of AI systems. Collaborated with AI teams to enhance response quality, user experience, and model reliability.