Miguel Collette is a Python software engineer with eight years' experience building data processing systems for cybersecurity and prior work across industry and research. Currently on CybelAngel’s Data Processing team, he focuses on extracting and shaping leak-related signals from large, noisy datasets to support threat detection. His background includes NLP and NLG research at Xerox, hands-on log analysis and frontend tweaks at Grass Valley, and a Master's in Artificial Intelligence from Université Pierre et Marie Curie. Comfortable across the stack, he blends academic techniques (finite state transducers, language models) with practical tooling like Elasticsearch and Logstash. Colleagues know him for turning complex algorithmic concepts into maintainable production code and for a pragmatic curiosity that spans from transport-network algorithms to customer-facing systems.
9 years of coding experience
4 years of employment as a software developer
Master's degree Artificial intelligence, Master's degree Artificial intelligence at Pierre and Marie Curie University
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