Ahmed Abozaid

Detail-oriented and efficient AI Data Annotator with hands-on experience working with Frontier LLMs and open-source AI ecosystems and a proven track record of labeling, categorizing, and cleaning large-scale datasets to train high-performing machine learning and generative AI models. Experienced in executing precise image bounding, semantic text categorization, and side-by-side model comparison tasks under strict quality guidelines. Combines an engineering background with technical literacy in Python and JSON to identify data anomalies, bring strong analytical thinking, strict guideline adherence, and a meticulous eye for quality to every annotation task.

AI Data Annotator / Evaluator (Project-Based) at highspring (2025-12 – 2026-03)

• Compared pairs of AI-generated responses and selected the better answer based on clarity, accuracy, and helpfulness — directly replicating RLHF-style preference annotation tasks.
• Categorized hundreds of text samples by intent, topic, and meaning (e.g., identifying questions, complaints, instructions) to support text classification model training.
• Reviewed structured datasets in JSON and CSV format ensuring clean, reliable training data.
• Labeled and described content from AI outputs across different task types (question answering, summarization, instructions), tagging each sample according to specific annotation guidelines.
• Maintained high consistency and accuracy across repeated annotation sessions, cross-checking outputs against rubrics and flagging edge cases for review.

Bachelor of Engineering in Electronics and Communications – Helwan University, Egypt (2024)