Automotive - AI Engineer

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. Qualifications

  Bachelors or Masters in Computer Science, Artificial Intelligence, Data Science, or related field Essential skills

  • 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 trouble-shooting skills using a structured documented approach
  • Excellent communication skills, both written and verbal
  • Confident, collaborative, self-motivated, determined energetic Desired skills
    • Specialization in one or more of these areas preferred: 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. Experience

      2 to 5 Yrs

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