Summary
Guillaume Sautière is a Staff Researcher at Qualcomm AI Research in Amsterdam with a decade of experience applying deep generative models to on-device video and audio compression. He progressed through research roles after Qualcomm’s acquisition of Scyfer, bringing practical expertise in data-efficient deep learning, active learning, and bridging research prototypes to edge deployments. His background spans biomechanics and machine learning certifications, reflecting a strong foundation in modeling physical systems and rigorous experimentation. Passionate about generative modeling, electronic music and clean code, he combines creativity with engineering discipline to squeeze more performance out of constrained hardware. Notably, he has applied reinforcement learning for chip power-performance management earlier in his career, showing a rare mix of systems-level and generative-model research.
10 years of coding experience
7 years of employment as a software developer
Expertise in Machine Learning, Expertise in Machine Learning at Coursera
Data Scientist, Data Scientist at DataQuest.io
Certification, Machine Learning, 8.5, Certification, Machine Learning, 8.5 at University of Amsterdam
Master of Science (M.Sc.), Biomechanical Engineering, Master of Science (M.Sc.), Biomechanical Engineering at Ecole nationale supérieure d'Arts et Métiers
Theoretical Physics and Mathematics, A+, Theoretical Physics and Mathematics, A+ at Lycée Chateaubriand Rennes