AI Machine Learning Optimization Engineer H/F
Listed on Stellantis’s official careers site. Posted March 2, 2023. Check that it is still open and apply there.
Apply on Stellantis’s careers site →Job description
Nous rejoindre, c'est intégrer une entreprise d'envergure mondiale. Mû par la recherche permanente de l'innovation et de l'excellence, pionnier et leader des technologies propres et de la mobilité durable, le Groupe entend rester à la pointe des grandes tendances qui font bouger le monde. Fort de son efficience, de son agilité et de son esprit d'équipe, le Groupe fait preuve d'exigence et d'audace pour définir la mobilité de demain.
Pour réussir ces transformations, l'entreprise a besoin de tous les talents. Rejoignez-nous ! Chez Stellantis, nous évaluons les candidats selon leurs qualifications, leurs mérites et les besoins du métier. Nous accueillons les candidatures des personnes de tout genre, âge, ethnie, nationalité, religion, orientation sexuelle, et handicap. La diversité de nos équipes nous permettra de mieux appréhender l'évolution des besoins de nos clients et de notre environnement futur.
Stellantis' AI team is expanding and offers exciting job opportunities for exceptional candidates to contribute to AI services and AI for autonomous driving. As a member of the Machine Learning Infrastructure team, you will be contributing to the development activities for new features and services. You will be taking part in optimizing our deep learning models before implementing on the ECU targets, using the available resources as cleverly as possible.
This position offers a high level of interaction with other AI development teams, and support entities within the group. The ideal candidate will have a solid experience of running Machine Learning trainings and validation, as well as setting up the tools implied in the associated workflows Basic Qualification
- Master of Science in Applied Physics, Math, Computer Science, Electrical/Computer/Automation Engineering, or related Engineering field.
- Engineering School
- Machine learning, deep neural networks infrastructure knowledge, inference engine knowledge
- Proficient in Python, C++
- Good communication skills in English language
Preferred Qualification
- Sound knowledge of at least one deep learning framework such as Tensorflow, Pytorch
- Knowledge or prior experience in deep learning networks optimization (Quantization, pruning, …)
- Knowledge of embedded computing, compiling and running code on embedded target systems.
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