Company

AMPERE SOFTWARE TECHNOLOGY

Job Description

Context and working environment In a rapidly changing technological context, the automotive industry is quickly moving towards autonomous driving and the Software-Defined Vehicle. This transition comes with major challenges, such as ensuring safety, mastering the complexity of driving environments, and managing colossal volumes of data. To meet these challenges, the Renault Group, through Ampere, places artificial intelligence at the heart of its strategy and performance for the development of Advanced Driver-Assistance Systems (ADAS) and Navigation On Autopilot (NOA). Among the initiatives aimed at ensuring the safety of these systems, rigorous evaluation of "end-to-end" AI models and identification of atypical or critical driving scenarios play a crucial role. This thesis work is part of this innovation approach around "Scenario Intelligence." By joining the Renault Group Engineering, you enter a domain with high technical, safety, and economic stakes.

Your missions This thesis subject aims to design innovative methods for classifying driving scenarios present in our driving data and rigorously evaluating the coverage of our databases (real or synthetic). The approaches developed will need to exploit latent spaces (embeddings) derived from AI to overcome the limitations of natural language, and rely on generative models (World Models) to compensate for the lack of critical data. The challenge of this validation is twofold: guaranteeing the safety of our systems through closed-loop tests on synthesized scenarios, while minimizing data acquisition costs and computing infrastructure. To achieve this, your missions will include:

• Conducting bibliographic research to establish a critical state of the art on Representation Learning applied to autonomous driving.

• Designing and training an encoding architecture (latent space) optimized to accurately model road dynamics.

• Experimental evaluation and benchmarking of this method on Renault's massive databases and on public reference datasets.

• Developing a strategy for generating missing scenarios (edge cases) using World Models.

• Scientific valorization of your work through patent drafting and publications for international conferences and journals.

Your profile You are a graduate (BAC+5, Master's degree or engineering school) with a specialization in Computer Science, Machine Learning, or Applied Mathematics. You have solid knowledge in Artificial Intelligence (Deep learning, vision models, generative architectures) as well as very good development skills in Python and integration of third-party code. Knowledge of embedded systems validation or autonomous driving would be a plus. You are autonomous, rigorous, and organized. You enjoy algorithmic research and have good writing and synthesis skills. You stand out for your motivation, your curiosity for complex scientific challenges, and your ability to be proactive. You have good interpersonal skills, communicate easily, and know how to work in a team (50% sharing between the company and the laboratory). Your level of English is an indispensable asset for evolving in scientific research (writing, conferences) and in a multicultural context within the Renault Group.

Job Family

Transverse

Contract Duration

36 months

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