Multi-modal AI Alignment & RLHF Workflows

A professional showcase of high-precision multi-modal data annotation and Reinforcement Learning from Human Feedback (RLHF) aimed at optimizing Large Language Model (LLM) performance. This workflow encompasses auditing speech-to-speech models for naturalness and adherence, refining computer vision through pixel-perfect image segmentation, and engineering complex reasoning benchmarks to ensure AI safety and output accuracy across diverse task domains.