Sergio Martínez Hamdoun
Machine Learning Engineer Computer Vision Airbus Global Graduate Program (Aggp) @Airbus Defence and Space
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WORK HISTORY
Machine Learning Engineer Computer Vision Airbus Global Graduate Program (Aggp) @Airbus Defence and Space
Getafe, ES
Architected end-to-end safety-critical AI solutions for computer vision tasks within the AVIENICS Team,establishing comprehensive frameworks for certifiable artificial intelligence systems in aerospace applications.Engineered advanced tools and automated processes were developed in to streamline development pipelines for certifiable AI solutions, enhancing workflow efficiency and ensuring compliance with safety-critical standards.Contributed to the development of photorealistic flight simulators using Unreal Engine 5, creating synthetic data generation capabilities that support AI model training and validation processes.Evaluated and integrated AI inference solutions across diverse embedded system architectures, optimizingperformance for both certifiable and non-certifiable platforms in aerospace environments.Collaborated with cross-functional teams to develop computer vision-based machine learning solutions, enabling automated task execution and advancing intelligent aerospace system capabilities.
EDUCATION
Universidad Politécnica de Madrid
Master's degree in Industrial Engineering, Industrial Engineering
Universidad Politécnica de Madrid
Master's degree in Automatic Control and Robotics, Industrial Engineering
Universidad de Málaga
Bachelor's degree in Industrial Engineering, Industrial Engineering
ABOUT SERGIO MARTÍNEZ HAMDOUN
Computer Vision & Machine Learning Engineer @ Airbus Defence and SpacePassionate about designing and deploying intelligent systems that perceive, learn, and act in real-world environments. With 3+ years of experience, I build end-to-end AI solutions—from sensor data processing and computer vision to robotics control and autonomous navigation—across diverse industries.My Core Expertise:• Machine Learning & Deep Learning: Developing scalable models for pattern recognition, predictive analytics, and decision-making using PyTorch, TensorFlow, and scikit-learn • Computer Vision & Perception: Architecting algorithms for object detection, image segmentation, 3D reconstruction, and scene understanding in applications ranging from inspection to AR/VR • Robotics & Autonomous Navigation: Designing control architectures and SLAM pipelines for mobile robots and drones, integrating ROS, Python, and C++ for robust real-time performance • End-to-End AI Systems: Leading the full AI lifecycle—data acquisition, preprocessing, model training, deployment (cloud & edge), and continuous improvement with MLOps practices • Cross-Functional Collaboration: Guiding interdisciplinary teams through agile development, bridging hardware, software, and algorithm design to deliver production-ready solutionsImpact Highlights:• Delivered multi-modal perception systems that fuse LiDAR, vision, and IMU data for reliable environment mapping • Implemented autonomous waypoint navigation for unmanned vehicles in GPS-denied environments • Established synthetic data generation workflows to accelerate model training and reduce annotation costsWhat Drives Me:I believe intelligent machines—combining AI, vision, and robotics—can unlock solutions to complex challenges in manufacturing, mobility, healthcare, and beyond. My mission is to lead technical teams that turn cutting-edge research into reliable, scalable products that make everyday life smarter and safer.Let’s connect! I’m always open to discussing AI engineering, robotics innovation, or collaboration on autonomy and perception projects.
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