AI Content Evaluation & Data Annotation for Conversational Models
AudioTranscription
Contributed to a data annotation and evaluation project focused on improving the accuracy, clarity, and contextual relevance of AI-generated content for conversational models. Responsibilities included reviewing and labeling text outputs based on predefined quality guidelines, identifying inconsistencies in tone, logic, and factual accuracy, and providing structured feedback to enhance model performance.
Performed comparative analysis of multiple AI responses, ranking outputs based on coherence, relevance, and user intent alignment. Applied strong attention to detail and analytical reasoning to ensure high-quality annotations across diverse content categories, including general knowledge, business communication, and web-related queries.
Contributed to a data annotation and evaluation project focused on improving the accuracy, clarity, and contextual relevance of AI-generated content for conversational models. Responsibilities included reviewing and labeling text outputs based on predefined quality guidelines, identifying inconsistencies in tone, logic, and factual accuracy, and providing structured feedback to enhance model performance. Performed comparative analysis of multiple AI responses, ranking outputs based on coherence, relevance, and user intent alignment. Applied strong attention to detail and analytical reasoning to ensure high-quality annotations across diverse content categories, including general knowledge, business communication, and web-related queries.
2025 - 2026