Summary
Thomas Schweizer is a software engineer specializing in machine learning and source-code analysis, with 11 years of experience building developer-facing tools and production systems. He combines academic rigor from UW and Université de Montréal—where his research produced practical advances in commit-untangling and bug fixing—with industry impact at AWS, MILA, and now Meta. He has shipped ML infrastructure and hyperparameter tooling used by top researchers, detected web vulnerabilities at scale, and led architecture and testing improvements for mission-critical multi-platform applications in de-mining operations. Comfortable at the intersection of SE, ML, and HCI, he pairs user-centered design with reproducible experimentation to make imperfect AI tools genuinely useful for developers.
11 years of coding experience
4 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at University of Washington
Master's degree, Computer Software Engineering, Master's degree, Computer Software Engineering at Université de Montréal
Bachelor's Degree, Software developpement, A, Bachelor's Degree, Software developpement, A at HEIG-VD
Certificat Fédérale de Capacité en informatique (Apprenticeship certificate in Computer Science), Networking, Hardware, Software, Project management, A, Certificat Fédérale de Capacité en informatique (Apprenticeship certificate in Computer Science), Networking, Hardware, Software, Project management, A at ETML
French, English, German