About Jérémy
English
Native or bilingual
French
Native or bilingual
Experience
- INEOFullstack DeveloperTELECOMMUNICATIONSSeptember 2025 - Today (9 months)Toulouse, FranceDevelopment of network gateways and other utility software for the conversion of IEC61850, HNZ, OPCUA protocols.A minimal test environment on a real platform is set up and the entire deployment architecture is also developed by the software client. The development itself is therefore accompanied by the DevOps part which includes automated containerization, automated deployment and automated testing. (CI/CD Github and Gitlab, Jenkins, VMWare esxi)
- Sorbonne UniversitéContractual Teacher-ResearcherSeptember 2025 - Today (9 months)Paris, FranceHigh-level university teaching in Computer Science at Sorbonne University, Licence / Master. Training in programming, networks, artificial intelligence and low-level computing for robotics.
- Sorbonne UniversitéPhD Student in AI RoboticsOctober 2020 - December 2023 (3 years and 2 months)Paris, FrancePhD in AI Robotics at the Intelligent Systems and Robotics Institute of Sorbonne University. This involves experimental studies and theoretical modeling of certain families of algorithms deployed on a multitude of centimeter-scale robots in interaction.
Recommendations
Be the first to recommend Jérémy
Help this freelancer shine by sharing your experience working together.
These freelancer profiles also match your criteria
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Education
- Master 2 Artificial Intelligence and Machine LearningAix-Marseille University2020Le parcours Intelligence Artificielle et Apprentissage Automatique (IAAA) introduit les avancées les plus récentes en intelligence artificielle et forme à l’exploitation des méthodes et techniques associées dans des applications innovantes. Les thèmes abordés sont l’apprentissage automatique (machine learning), l’apprentissage profond (deep learning), le traitement automatique du langage naturel (NLP), la modélisation et de la résolution de problèmes à base de contraintes, et la représentation et le traitement des connaissances. Ces thèmes s’inscrivent notamment dans le cadre de la science des données et de l’informatique fondamentale.