François-xavier Aubet is a Research Engineer at Google DeepMind with nine years’ experience applying machine learning to real-world systems, from supply-chain forecasting at Amazon to DevOps anomaly detection and NFL analytics at AWS. He holds an MSc in Machine Learning from UCL and dual BSc degrees from TUM, graduating near the top of his class, and has a track record of turning research into production-ready services. At DeepMind he focuses on bridging pre-training and post-training for large models, building on prior work in time-series forecasting and probabilistic anomaly detection. He combines deep technical expertise in ML and systems with hands-on engineering across Python, TensorFlow/Keras, and embedded C for robotics projects. Not obviously visible from his title, he has experience designing science methods for product launches and mentoring interns while shipping first-of-kind algorithms. Based in Stony Stratford, he thrives at the intersection of research rigor and product-driven deployment.
9 years of coding experience
4 years of employment as a software developer
Baccalauréat, Baccalauréat at Lycée francais de vienne
Stiftung Bayerische EliteAkademie
Bachelor of Science (B.Sc.), Electrical and Electronics Engineering, Grade: 1,7 (A) (Part of the best 14%), Bachelor of Science (B.Sc.), Electrical and Electronics Engineering, Grade: 1,7 (A) (Part of the best 14%) at Technische Universität München
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François-xavier Aubet - Research Engineer at Google DeepMind