AI Machine Learning Optimization Engineer

About the role

Stellantis' AI team is expanding and is looking for an AI Machine Learning Optimization Engineer to join its Machine Learning Infrastructure team. The role contributes to developing new AI features and services, including optimizing deep learning models before they are deployed on ECU targets. It involves close interaction with other AI development teams and support entities within the group.

Key responsibilities

• Contribute to the development of new features and services for AI services and AI for autonomous driving.
• Optimize deep learning models before implementation on ECU targets, making efficient use of available resources.
• Work closely with other AI development teams and group support entities.

Required profile

• Master's degree in Applied Physics, Mathematics, Computer Science, Electrical/Computer/Automation Engineering or a related engineering field, or an engineering school diploma.
• Solid experience running machine learning training and validation, and setting up the tools used in the associated workflows.
• Minimum 5 to 10 years of experience.
• Fluent English (C1).

Required skills

• Knowledge of machine learning and deep neural network infrastructure, and of inference engines.
• Proficiency in Python and C++.
• Preferred: knowledge of a deep learning framework such as TensorFlow or PyTorch.
• Preferred: experience in deep learning network optimization (quantization, pruning, etc.).
• Preferred: knowledge of embedded computing and running code on embedded target systems.