Data Annotator

Data Annotators label and categorize training datasets for machine learning models, applying structured annotation guidelines to text, images, audio, and video data to create high-quality ground truth for supervised learning systems. They review model outputs for quality assurance, identify edge cases, and participate in feedback loops that improve AI system accuracy. LinkedIn named Data Annotator the fourth fastest-growing role in 2026, driven by the massive data requirements of foundation model training.