AI Training Specialist
I worked on a beginner-level AI data labeling project focused on the IT/SaaS industry, specifically supporting text-based models and question-answering systems. The scope of the labeling involved preparing and annotating written content such as product documentation, FAQs, and customer support queries to help train models to better understand technical language and respond accurately to user questions. The project size included a moderate dataset consisting of hundreds to a few thousand text samples. My tasks involved classifying queries by intent, tagging key entities (such as software features, tools, and technical terms), and matching questions with the most relevant answers. I also assisted in reviewing and refining labeled data to ensure consistency with the provided guidelines. In terms of quality measures, I followed detailed annotation instructions closely, double-checked my work for accuracy, and paid attention to edge cases where questions could have multiple interpretations. I maintained consistency in labeling, adhered to formatting standards, and incorporated feedback from reviewers to improve performance over time.