Contractor, Mercor Intelligence (LLM training support via prompt-response and simulations)
Created and audited prompt-response datasets to support model training and RLHF pipelines. Authored high-fidelity prompt-response pairs and built multi-tier rubrics to evaluate model outputs for alignment, factuality, and decision quality. Identified model failure modes and proposed refinements to improve interpretability, strategic coherence, and operational realism. • Delivered high-resolution domain analysis for AI research labs in GM and operations contexts. • Designed structured simulations of real-world workflows for training signal generation. • Produced ~120 prompt-response pairs per two-week sprint with rubrics. • Evaluated outputs for alignment, factuality, and decision quality; iterated on training improvements.