AI Training and Data Labeling Specialist
Transitioned into AI training and RLHF by providing rating, ranking, hallucination detection, and fact-checking annotations for LLM outputs. Leveraged software engineering expertise to interpret and follow complex labeling guidelines for high-quality data creation. Focused on tasks such as entity extraction and semantic segmentation, ensuring strict rule adherence in AI-driven projects. • Performed entity recognition, sentiment analysis, and consistency validation for natural language text corpora. • Conducted model evaluation for output quality and checked against hallucinations and factual consistency. • Applied structured thinking to quickly learn new taxonomies and edge case handling for diverse datasets. • Maintained high standards through peer review and iterative QA for training and evaluation data.