Summary
Michael Sutton is a computer vision and deep learning engineer with nine years of hands-on experience building prototype-to-production vision systems at YOOBIC and Paris Digital Lab. Trained at École Normale Supérieure (MVA) and École Centrale Paris with a strong mathematics background from Université Paris Dauphine, he blends rigorous theory with practical engineering in Python, C++, TensorFlow, PyTorch and OpenCV. He thrives in agile, sprint-driven environments that turn rapid prototypes into deployable features and has a track record of designing CV models for real-world end-user experiences. Beyond models, he has operational experience in network and systems administration and early IT teaching, giving him a pragmatic appreciation for deployment, scalability and user-facing constraints. Based in Paris, he brings a research-caliber mindset to applied problems, often favoring elegant mathematical solutions over brute-force engineering.
10 years of coding experience
1 year of employment as a software developer
Master of Engineering student, Master of Engineering student at Ecole Centrale Paris
Bachelor’s Degree, Bachelor of Science (BS), Applied Mathematics, Highest honours, Bachelor’s Degree, Bachelor of Science (BS), Applied Mathematics, Highest honours at Université Paris Dauphine
Master of Science - MS, Mathematiques Vision Apprentissage (MVA) Machine Learning and Computer Vision, Mention Très Bien (Highest Honours), Master of Science - MS, Mathematiques Vision Apprentissage (MVA) Machine Learning and Computer Vision, Mention Très Bien (Highest Honours) at École Normale Supérieure Paris-Saclay
French, English, Spanish, Hebrew