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CVAT
Data Annotation Tech
Label Studio
Scale AINo subject matter listed
Computer Code Programming
Text
VideoI’m an AI Evaluation & Data Annotation Specialist with hands-on experience shaping the performance, safety, and reliability of large language models (LLMs) and computer vision (CV) systems. Over the past several years, I’ve contributed to cutting-edge projects in: NLP & Chatbot Alignment – evaluating multi-persona chatbots, ensuring tone consistency, refining responses, and conducting safety tests to prevent harmful or illegal outputs. Prompt Engineering & Compliance – designing and testing system prompts, validating multi-turn compliance, and improving behavioural reliability. Persona & Memory Testing – assessing long-form conversations to ensure models respect assigned personas and consistently integrate user-specific memories. Mathematical Reasoning – creating and reviewing educational content, from grade school to university-level maths, ensuring truthfulness, clarity, and cultural/linguistic alignment. Computer Vision – testing models with adversarial cases, refining outputs for tiny details, and building high-quality annotated datasets (bounding boxes, polygons, segmentation) with CVAT and Label Studio. What ties my work together is a commitment to making AI systems safer, more accurate, and more aligned with human needs. Whether it’s strengthening RLHF pipelines, improving dataset quality, or fine-tuning system prompts, I bring a mix of technical rigour, bilingual expertise (Arabic & English), and a problem-solving mindset.
Fine tuning Egyptian Arabic chatbot and correct the response if it does not align with project rules.
Evaluating the response of the generated code-related responses and prompts. Correct the model response if does not align with the rules of the project.
Bachelor in law and economics, Law and economics
AI Evaluation and Alignment Specialist
