AI Research Assistant (Data Labeling & AI Training)
Developed structured problem sets to train and evaluate large language models in mathematical and computational reasoning. Refined LLM-generated responses with subject matter experts to improve accuracy in engineering and scientific domains. Conducted detailed error analysis on AI outputs to identify and resolve biases and inconsistencies. • Created learning tasks for AI models involving mathematical, statistical, and engineering problems • Worked alongside academic researchers to define labeling guidelines • Preprocessed textual datasets using Python scripting for enhanced AI training • Contributed to advancement of domain-specific datasets for machine learning