RLHF Evaluator
At LibanReach, I lead tasks that require understanding and assessment of the reasoning quality of AI-generated outputs, contributing directly to reinforcement learning from human feedback processes. This includes ranking possible responses, evaluating alignment with user intent, and annotating reasoning flaws or strengths. My contributions help guide how AI agents interact and escalate decisions based on set autonomy ceilings. • Conducted RLHF evaluations of LLM prompt and response pairs. • Ranked multiple system outputs for relevance and practical value. • Identified edge cases and provided annotations for model retraining. • Led alignment and escalation scenario evaluations for executive AI agents.