Summary
Thomas Schillaci is a machine learning engineer and founder with 11 years of experience building production ML systems and cloud-native tooling. He co-founded a stealth startup in San Francisco after leading the design and deployment of an internal ML stack at Dassault Systèmes that integrated 60+ foundation models, accelerated training 30x and inference 50x, and generates over 50 billion tokens annually. His background spans industrial applications—developing deep learning pipelines for turbojet anomaly detection at Safran—and enterprise consulting, where he managed large international programs and delivered BI training. He combines hands-on full-stack skills (AWS, Kubernetes, Docker, PyTorch, Keras, Flask) with product-minded orchestration of model registries, experiment tracking and high-performance inference services. A Georgia Tech and IMT Atlantique alumnus, he blends academic rigor with practical deployment experience and a penchant for simplifying complex ML workflows. Colleagues know him for turning experimental research into reliable, scalable production systems rather than just prototypes.
11 years of coding experience
3 years of employment as a software developer
Master of Science Computer Science, Master of Science Computer Science at IMT Atlantique
Master of Science Computer Science, Master of Science Computer Science at Georgia Institute of Technology
English, Spanish, French, Japanese