Principal AI Engineer

Valeo is a tech global company, designing breakthrough solutions to reinvent the mobility. We are an automotive supplier partner to automakers and new mobility actors worldwide. Our vision? Invent a greener and more secured mobility, thanks to solutions focusing on intuitive driving and reducing CO2 emissions. We are leader on our businesses, and recognized as one of the largest global innovative companies.

Valeo anSWer Product Line is a world leader in providing advanced driver-assistance (ADAS) and automated driving/parking systems. The AI Platform team is responsible for developing custom-built, state-of-the-art neural architectures designed to leverage the full power of today's most advanced multi-core automotive embedded platforms and Neural Processing Units (NPUs). Moving beyond traditional modular perception pipelines, the team applies state-of-the-art End-to-End (E2E) deep learning, imitation learning, and reinforcement learning to directly map multi-modal sensor inputs to vehicle control and trajectory planning. We specialize in redefining the state-of-the-art in AI, leveraging large-scale data and foundational driving models to deliver next-generation, fully differentiable automated driving systems for leading global OEMs. 

As a Principal AI Engineer, you will be responsible for the architectural design of end-to-end deep learning solutions enabling the next generation of automated driving and parking platforms. Working as part of a multidisciplinary team, you will utilize deep domain knowledge to technically guide the development of holistic, sensor-to-action AI models. You will be responsible for the design of state-of-the-art E2E algorithms, leveraging substantial driving datasets, behavioral cloning, and closed-loop simulation. You will be expected to remain at the absolute forefront of technological developments in the rapidly expanding fields of large driving models, embodied AI, Vision-Language-Action (VLA) models, and edge compute optimization. 

• →Architect E2E Driving Models: Lead research and design for fully differentiable, sensor-to-control neural networks powering automated driving and parking.
• →Direct AI Governance & Alignment: Chair the AI Technical Steering Committee to approve designs, unify network backbones, and guide legacy algorithm migration.
• →Guide Hardware-Software Co-Design: Partner with embedded engineering teams to inform SoC partitioning, pipelining, and AI optimization strategies (quantization, pruning, memory bandwidth) for multi-core ARM, DSP, and dedicated NPU hardware. 
• →Deliver RFI/RFQ Technical Architectures: Spearhead novel AI system proposals for pre-development programs and commercial vehicle bids.
• →Support Safety & Regulatory Compliance: Collaborate with systems and safety engineering to align E2E architectures with automotive safety standards (e.g., ISO 21448 SOTIF) and AI regulations, advising on model interpretability and safety boundaries. 
• →Drive Research & Intellectual Property: Lead university research partnerships and generate invention disclosure memos to secure strategic patents.

• Relevant BSc, BEng, or PhD (Mathematics, Physics, Computer Science, or Engineering) with 7+ years of applied experience in deep learning and autonomous systems.
• Deep understanding of modern machine learning architectures (Vision Transformers, Sequence-to-Sequence models, BEV networks, and Vision-Language-Action models).
• Algorithm development experience in end-to-end autonomous driving, imitation learning, reinforcement learning, or advanced trajectory planning.
• Extensive experience with edge AI hardware, heterogeneous SOCs, and Neural Processing Units (NPUs) for deploying large-scale models.
• Proficiency in deploying AI models to embedded platforms.
• Experience with large-scale ML data pipelines, auto-labeling, and driving data curation.
• Proven track record in the automotive, robotics, or autonomous vehicle industry.
• Excellent English language communication skills, both written and verbal.
• High level of innovation, motivation, and technical leadership.
• Academic publications and/or active IP/patents in the fields of deep learning, automated driving, or robotics.

• Experience with closed-loop autonomous driving simulators (e.g., CARLA, internally developed simulation engines) and neural simulators (e.g., NeRFs, 3D Gaussian Splatting for driving).
• Deep understanding of modern ML frameworks (PyTorch 2.x) and MLOps pipelines for continuous training of E2E models.

Join Us !
Being part of our team, you will join:
- one of the largest global innovative companies, with more than 20,000 engineers working in Research & Development
- a multi-cultural environment that values diversity and international collaboration
- more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
- a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development

More information on Valeo: https://www.valeo.com