Multi-Domain AI Training & Code Evaluation for LLM Fine-Tuning
Computer Code Programming
RLHFOver the past 2+ years, I have contributed to multiple AI training and data labeling projects focused on improving the performance, reliability, and safety of large language models (LLMs). My work has included evaluating model outputs across coding tasks (Python, JavaScript, TypeScript, Java, SQL), writing high-quality prompts, designing binary rubrics for objective model evaluation, and producing detailed feedback used for supervised fine-tuning and RLHF pipelines. I have experience identifying hallucinations, logical errors, and code quality issues in AI-generated responses, ensuring that final datasets meet strict accuracy and formatting standards. I am familiar with tools such as Git/GitHub, Docker, and containerized workflows, and consistently follow detailed annotation guidelines to deliver consistent, audit-ready output at scale.