Automotive - AI Engineer

Role Overview

As an artificial intelligence engineer, you will be responsible for the development of state of the art algorithms enabling Automated Driving Assistance Systems. Examples of such algorithms include: VRU detection, localization, traffic sign detection, lane detection, park slot detection, object detection and classification & scene understanding.

Responsibilities

• Research, develop, benchmark, test and document state of the art algorithms for autonomous driving.
• Research new vision and other sensor technology, ideas, and approaches.
• Support Intellectual Property activities and generate Invention Disclosure Memos to facilitate patent applications.
• Contribute to design reviews across algorithm teams.
• Consider next generation algorithms and new business opportunities.
• Develop algorithms with a view to implementing on embedded platforms.
• Represent Valeo anSWer at various Industry Working Groups and at Conferences.
• Support the design and implementation of in-company training sessions in your area of expertise.
• Strive to improve competencies in the field of automotive sensors based ADAS, DL frameworks & techniques.
• Identify inefficiencies and suggest/implement improvements within the current processes used in algorithm development.

Requirements

• Bachelors or Masters in Computer Science, Artificial Intelligence, Data Science, or related field.
• Strong knowledge of deep learning concepts and computer vision.
• Experience with object detection models such as YOLO and semantic segmentation.
• Expertise in Python programming and strong software engineering practices.
• Proficiency with version control tools such as Git, Bash scripting, and automation.
• Excellent analysis & troubleshooting skills using a structured documented approach.
• Excellent communication skills, both written and verbal.
• 2 to 5 years of experience.

Nice to Have

• Specialization in Transformers, Multi-task learning, Optimization, and Multi-modal models.
• Experience designing complex systems with multiple algorithms or modules.
• Academic publications in top-tier conferences such as CVPR, NeurIPS, ICCV, and ECCV.
• Experience with commercially deploying algorithms in robotics, LIDAR, camera systems, or sensor fusion.
• Experience developing algorithms for autonomous and/or real-time systems.
• Deep knowledge of camera systems.
• Automotive industry experience.

Skills

• Python
• PyTorch
• Computer Vision
• Deep Learning
• Git