Camille Barneaud is a seasoned technology leader and CTO with 14 years of experience building data-driven products and scaling engineering teams from prototype to production. As co-founder and CTO of Railee and current CTO at HOURRAIL!, he is reinventing long-distance train travel by combining product vision with hands-on architecture and data engineering. His background spans fraud detection and ML platforms at Shift Technology, deep technical prototyping in R&D, and founding climate-focused and industrial-risk SaaS ventures, showing strong cross-domain expertise. Camille blends full-stack software skills with applied data science, having helped build notable tooling like Wappalyzer and led reporting and detection systems that became business growth engines. Based in Paris, he pairs formal training from Télécom Paris and Mines d'Alès with entrepreneurial grit from Founder in Residence roles, investor activity, and early-stage product launches. A pragmatic builder, he often moves between code, architecture, and fundraising—uniting technical depth with a taste for mission-driven companies.
14 years of coding experience
5 years of employment as a software developer
Concours réussi Hardcore training to C & Shell UNIX, Concours réussi Hardcore training to C & Shell UNIX at 42 Paris
M1 - Data Science Mathématiques et informatique, M1 - Data Science Mathématiques et informatique at Télécom Paris
MOOC - Introduction to a Web of Linked Data Computer Science, MOOC - Introduction to a Web of Linked Data Computer Science at uTOP : Université de Technologie Ouverte Pluripartenaire
Preparatory school to « Grandes Ecoles » Major MP (Maths Physics) minor Computer Science Maths & Physics, Preparatory school to « Grandes Ecoles » Major MP (Maths Physics) minor Computer Science Maths & Physics at Lycée Thiers
Master of Science in Engineering Engineering and Management of Complex Systems, Master of Science in Engineering Engineering and Management of Complex Systems at Ecole des Mines d'Alès
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Contributions:8 commits, 11 pushes, 5 branches in 3 months
pytorchmaskdetectiondeep-learningretinanet
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