AI Model Training Specialist focused on RLHF and quality analytics (as described in professional summary)
Performed evaluation of natural-language model outputs using rigorous criteria for veracity, security, and coherence as part of RLHF-style quality analytics. Assessed responses for hallucinations and factual accuracy while ensuring adherence to complex guidelines and policies. Documented findings with metrics-driven quality checks to support fine-tuning improvements. • Verified truthfulness and consistency of generated responses • Monitored safety/security and guideline compliance • Checked coherence and usability for end users • Supported fine-tuning by mitigating hallucinations