OUTLIER MULTIMANGO
Outlier’s Multimango project involved producing and evaluating large volumes of high‑quality training data for AI models. My work included creating natural user prompts, writing clear and accurate human‑like responses, and performing detailed labelling tasks such as ranking AI outputs, identifying errors, and providing justification based on strict evaluation rubrics. The project operated at scale, with thousands of tasks requiring consistency, accuracy, and adherence to quality and safety guidelines. Throughout the project, I maintained strong attention to detail, followed structured scoring frameworks, and ensured every submission met Outlier’s standards for clarity, correctness, and natural language authenticity.