AI trainer at revelo Claude AI
I have worked on multiple data labeling and annotation projects, particularly focused on improving AI model performance and output quality. AI Training & Prompt Annotation (Claude AI – Revelo Platform): I contributed to training large language models by creating, refining, and evaluating prompts and responses. This included ranking outputs, correcting inaccuracies, and applying structured guidelines to improve reasoning, coherence, and factual correctness. Text Annotation & Classification: Labeled datasets for NLP tasks such as sentiment analysis, intent classification, and content moderation. I ensured consistency by following strict annotation guidelines and resolving ambiguous cases with logical reasoning. Data Quality Review & Validation: Performed quality checks on annotated datasets to ensure accuracy and reduce bias. This involved cross-checking labels, identifying inconsistencies, and suggesting improvements to annotation workflows. Structured Data Formatting: Organized and annotated data into structured formats (JSON/CSV) for machine learning pipelines, ensuring it was clean, standardized, and ready for training. These experiences have strengthened my attention to detail, ability to follow complex guidelines, and understanding of how high-quality labeled data directly impacts AI model performance.