AI Data Annotator
Performed search engine evaluation, LLM response ranking, and AI output quality assessment across multiple AI training platforms. • Analyzed 500+ search engine outputs daily, applying rubric-based scoring to ensure relevance, accuracy, and quality for AI applications. • Conducted data annotation, preference ranking, and pairwise comparisons to support RLHF pipelines and LLM fine-tuning. • Sustained 98% annotation accuracy rate across all platforms, consistently exceeding quality thresholds. • Evaluated multimodal content including text, image, and search outputs for relevance, factual accuracy, and user intent alignment. • Delivered accurate audio transcription services via Rev, TranscribeMe, QA Word, and Upwork, maintaining high quality and turnaround standards.