Freelance AI Data Contributor (Remote) — AI training and LLM evaluation for data annotation and quality assurance
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TextEvaluated and ranked large language model (LLM) outputs by accuracy, relevance, reasoning quality, safety, and alignment with user intent. Performed fact-checking and research verification of AI-generated content to support high-quality, reliable training data. Reviewed, labeled, and classified complex datasets, identifying inaccuracies, logical inconsistencies, and hallucinations with actionable feedback. • LLM output ranking and quality scoring based on guideline criteria • Dataset validation, labeling, and classification for training consistency • Hallucination and logical-reasoning error detection with detailed notes • Creation of evaluation reports and justification analyses for model improvement
2024 - Present