AI Data Trainer & Quality Analyst
Trained and evaluated large language models by labeling 2,500+ data points daily with 99.2% accuracy, improving model performance for major tech clients. Performed sentiment analysis, entity recognition, and prompt response scoring to reduce error rates by 35%. Followed and refined training guidelines while collaborating with global teams to ensure consistent labeling quality. • Labeled 2,500+ LLM-related data points per day to support model training. • Conducted sentiment analysis and entity recognition tasks for data enrichment. • Scored prompt-response quality and performed evaluation to guide improvements. • Collaborated via Slack and Zoom to refine guidelines and onboard annotators.