Available to hire
Hi there! I’m Abdulrahman, a curious AI/ML engineer blending robotics, computer vision, and language models to deliver practical, scalable AI solutions. I enjoy turning complex concepts into actionable plans, collaborating across disciplines, and shipping production-grade systems that users actually love.
Currently pursuing an MSc in Robotics & Artificial Intelligence at the University of Glasgow, and I’m excited to apply my skills in ML engineering and AI-powered automation across industries.
Skills
Experience Level
Language
English
Fluent
German
Beginner
Spanish; Castilian
Beginner
Work Experience
Applied Machine Learning Intern at Zenimal
December 1, 2024 - October 9, 2025Developed a production-ready LM-powered RAG-based AI support agent, reducing response time from 24 hours to under 2 minutes. Collected, filtered, and cleaned business data to build a structured knowledge base with contextual relevance. Evaluated system performance using intent recognition and slot-filling metrics to ensure high accuracy. Monitored deployed system by analyzing user transcripts to identify hallucinations and optimize agent behavior. Iteratively improved performance through prompt engineering, fallback handling, and retrieval enhancements.
Founder | AI Automation Agency at AI Engineers
December 1, 2024 - October 9, 2025Founded and led an AI automation agency delivering production-grade LM-based automation solutions across industries. Drove end-to-end product strategy, client discovery, and delivery of AI-powered automation.
Machine Learning Engineer Intern at New Tom LLC
August 1, 2023 - October 9, 2025Engineered a biometric authentication system using Python, OpenCV, and Raspberry Pi, achieving 86% accuracy in vein pattern recognition. Collected and labeled palm image datasets; applied data augmentation (rotation, scaling, lighting) to improve generalization. Designed, trained and deployed real-time object detection using KNN, YOLO X and PyTorch, leveraging AWS SageMaker for edge inference. Created REST APIs using AWS Lambda to serve ML models and connect them to a live web portal.
Machine Learning Research Assistant at United Arab Emirates University
August 1, 2022 - October 9, 2025Designed 1D CNN-based classification models for biomedical signal processing; improved accuracy from baseline to 75% using Optuna tuning. Conducted full ML lifecycle from exploratory data analysis to model validation, contributing to AI-driven healthcare research. Used model interpretation to identify influential features and collaborated with cross-functional teams to enhance clinical applicability. Dissertation: Multi-Iterative Retrieval-Augmented Generation (RAG).
Applied Machine Learning Intern at Zenimal
December 2, 2024 - October 9, 2025Developed and deployed a production-ready LLM-powered RAG-based AI support agent, reducing response time from 24 hours to under 2 minutes. Collected, filtered, and cleaned business data to build a structured knowledge base to improve contextual relevance. Evaluated system performance using intent recognition and slot-filling metrics, and monitored transcripts to identify hallucinations and optimize agent behavior. Iteratively improved the system through prompt engineering, fallback handling, and retrieval improvements.
Founder & AI Engineer at Sator AI Agency
December 1, 2024 - October 9, 2025Founded and led an AI automation agency delivering production-grade LLM-based automation solutions across industries. Conducted discovery sessions to assess AI maturity, defined client needs, and prioritized high-impact solutions. Translated complex AI concepts into actionable business strategies. Designed AI adoption roadmaps and scalable system architectures tailored to business needs. Acted as the main technical advisor bridging non-technical stakeholders and technical implementation teams. Collaborated with a small team to design, develop, and deploy AI solutions.
Machine Learning Engineer Intern at Newtowns LLC
August 1, 2023 - October 9, 2025Engineered a biometric authentication system using Python, OpenCV, and Raspberry Pi, achieving 86% accuracy in vein-pattern recognition. Collected and labeled palm-image datasets; applied data augmentation to improve model generalization. Designed, trained and deployed a real-time object detection model using KNN, YOLO X, and PyTorch; leveraged AWS SageMaker for edge inference. Implemented OpenSearch-based feature indexing and similarity search for palm-vein workflows. Created REST APIs using AWS Lambda to serve ML models and connect them to a live web portal.
Education
M.S. in Robotics & Artificial Intelligence at University of Glasgow
September 1, 2024 - September 1, 2025Master of Science in Robotics & Artificial Intelligence at University of Glasgow
September 1, 2024 - September 1, 2025Qualifications
Industry Experience
Software & Internet, Media & Entertainment, Professional Services, Education, Healthcare
Skills
Experience Level
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