AI Data Annotation & QA Contributor
Internal Proprietary ToolingTextClassificationText Generation
The role involved text annotation and response evaluation for AI training projects. Labeled datasets followed strict taxonomy and formatting rules, enhancing model training accuracy. Regular quality audits were conducted to ensure guideline adherence and consistency. Collaborative efforts aimed to address edge cases and improve decision rules for label clarity.
• Worked on multiple AI training projects involving data labeling, QA checks, and guideline-based evaluation.
• Labeled datasets by following strict taxonomy and formatting rules for model training.
• Reviewed AI-generated answers for correctness, completeness, and reasoning consistency.
• Classified user queries by intent and topic relevance to improve model routing.
The role involved text annotation and response evaluation for AI training projects. Labeled datasets followed strict taxonomy and formatting rules, enhancing model training accuracy. Regular quality audits were conducted to ensure guideline adherence and consistency. Collaborative efforts aimed to address edge cases and improve decision rules for label clarity. • Worked on multiple AI training projects involving data labeling, QA checks, and guideline-based evaluation. • Labeled datasets by following strict taxonomy and formatting rules for model training. • Reviewed AI-generated answers for correctness, completeness, and reasoning consistency. • Classified user queries by intent and topic relevance to improve model routing.
2023