Summary
Pierre D'istria is a Machine Learning Engineer with a decade of hands-on experience blending physics, computer science and production ML to deliver end-to-end systems from research prototypes to deployed products. He has built AutoML pipelines, serverless architectures handling millions of sensor messages, and ultra-low-power ML inference in C for microcontrollers—work that spanned Cartesiam through its acquisition by STMicroelectronics. His background in experimental physics and astrophysics informs a pragmatic, measurement-driven approach: he has built instruments for exoplanet hunting, processed large multimodal datasets at MILA, and applied plasma science in materials work. Comfortable bootstrapping codebases or scaling mature products, he’s finishing an MSc in AI and is particularly drawn to applying deep learning and generative models to scientific domains like drug discovery, space and energy. Passionate about practical innovation, he combines research rigor with product delivery to turn novel algorithms into reliable, real-world systems.
10 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Physics and Computer Science, Bachelor's degree, Physics and Computer Science at Université de Montréal
Mechanical Engineering, Mechanical Engineering at Arts et Métiers ParisTech - École Nationale Supérieure d'Arts et Métiers
Master of Science - MS, Artificial Intelligence, Master of Science - MS, Artificial Intelligence at University of Leeds
French, English