Job Details

Senior AI Machine Infrastructure

Fiat Chrysler Automobiles
Auburn Hills, Michigan, United States
Build your brand. Tell your story. Take advantage of a rare opportunity to create something new and original. At Stellantis, we're breaking with the past and launching a new software organization built from the ground up. The Stellantis Software organization (SWX) was established in 2021 and brings an entirely new vision to the driving experience. Our mission is to design the most captivating experiences in Mobility, bringing "tomorrow's" tech innovations closer to today, every day. If you're ready to help lead this automotive technology transformation, we want to hear from you. Visit to learn more. Stellantis was founded in 2021 as the result of a merger between Fiat Chrysler Automobiles and PSA Groupe. For more information, visit:

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 senior member of the Machine Learning team, you will be contributing to the development activities for new features and services. You will be responsible for implementing the HW infrastructure for our AI development team, making them evolve to adapt to needs.

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 setting up and running large computation infrastructures. Basic Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering or related degree field
  • A minimum of 8 years of related experience
  • Knowledge of HPC HW technologies (computing, networking, ...)
  • Operational knowledge of Linux systems administration
  • Proficient in Python, Linux, basic command of C++
  • Good communication skills
Preferred Qualifications:
  • Master's in Applied Physics, Math, Computer Science, Electrical/Computer/Automation Engineering
  • Having already managed Machine Learning infrastructures
  • Sound knowledge of at least one deep learning framework such as Tensorflow, Pytorch
  • Knowledge of workflow tools administration (MLFLow, DVC, Jenkins, ...)
  • Knowledge of scheduling tools (Slurm, Kubernetes)

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