At Outlier AI, I evaluate and annotate datasets for generative AI model training, following accuracy and guideline requirements. I assess prompt quality, translation accuracy, and culturally localized responses in Arabic and English.
I also identify reasoning, mathematical, and logical errors in AI-generated outputs through evaluation and verification. My work focuses on improving response quality and model reliability.
During my Data Engineering Trainee experience with Digital Egypt Pioneers Initiative (DEPI), I worked on data cleaning, ETL workflows, and SQL queries. In projects, I developed a Streamlit application for testing and visualizing classification models, and a Java file storage application with authentication and SHA-256 hashing.
