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@ayahani
AI Engineer specializing in multimodal LLMs, computer vision, and generative AI.
I am an AI Engineer with three years of hands-on experience building multimodal large language models (MLLMs), computer vision systems, NLP pipelines, and generative AI solutions. I focus on designing scalable ML systems and fine-tuning models to meet real-world requirements.
My projects include a multimodal driver behavior evaluation pipeline—where I fine-tuned MoViNet-A2, used YOLOv8, integrated Gemini Flash 2.5, and built scene interpretation with a visual vector database and ChromaDB—and an image-to-speech system that produces Arabic audio descriptions from images.
I continually improve models using real-time feedback and emphasize robust, data-driven solutions that deliver measurable impact. My technical toolkit spans PyTorch, TensorFlow, Hugging Face, OpenCV, Scikit-learn, and data tools such as Pandas and NumPy.
I hold a Bachelor of Engineering in Computer and Systems and have completed several certifications in generative AI, deep learning, and data science. I am motivated to join teams that push the boundaries of multimodal AI and deploy practical, user-facing intelligent systems.
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Work history, roles, and key accomplishments
Self Employed
Designed and deployed multimodal LLM and computer vision pipelines including fine-tuning models and building RAG systems to evaluate driver behavior and generate Arabic image-to-speech outputs.
Degrees, certifications, and relevant coursework
Bachelor of Engineering, Computer and Systems Engineering
2020 - 2025
Grade: GPA: 3.5
Bachelor of Engineering in Computer and Systems Department with a GPA of 3.5, focusing on AI and machine learning topics.
Software and tools used professionally
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