Have independent AI data labeling and model optimization experience
Have independent AI data labeling and model optimization experience. Responsible for business test dataset sorting, manual data labeling, quality audit and data cleansing for internal LLM testing scenarios, including test dialogue sample labeling, vulnerability text classification, test intent tagging and bad-case data screening. Standardize labeling rules combined with prompt iteration outcomes, optimize RAG corpus data quality, filter noisy and invalid corpus data, assist in fine-tuning vertical testing LLM, reduce agent misjudgment rate in automated testing tasks, and improve the accuracy of AI-generated test cases and risk identification results.
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