As an AI Trainer, I specialize in refining large language models through Reinforcement Learning from Human Feedback (RLHF) and strategic prompt engineering. My daily work involves crafting complex, multi-turn prompts to stress-test model reasoning and meticulously ranking model outputs based on accuracy, tone, and safety. I have a proven track record of reducing model hallucinations and bias by providing high-quality, annotated datasets and performing "red-teaming" to identify edge-case failures. By collaborating closely with machine learning engineers, I bridge the gap between raw data and human-centric AI, ensuring that every response the model generates is not only factually correct but also helpful and ethically aligned.