Mobileye
Mobileye
Mobileye develops advanced driver-assistance systems and autonomous driving technology for the automotive industry. The company combines computer vision, artificial intelligence, proprietary hardware, and software to support vehicle safety across applications ranging from driver assistance to autonomous operation. Its systems have been deployed in more than 190 million vehicles, reflecting Mobileye’s role in bringing vision-based automotive technologies to large-scale production.

Applied AI Researcher, Visual GenAI at Mobileye (Hybrid, Israel)

Advance visual GenAI, diffusion models, and computer vision for Mobileye’s autonomous driving technology. Build synthetic-data solutions using proprietary datasets and large-scale computing infrastructure.

Description

  • Lead the full development lifecycle, from training generative models to adapting state-of-the-art architectures for real-world autonomous driving applications.
  • Research, assess, and enhance GenAI and computer vision models through scalable, clean Python implementations.
  • Partner with AI researchers and perception teams to apply synthetic data in real-world AI systems.
  • Track emerging developments in artificial intelligence, generative modeling, and computer vision.
  • Create GenAI solutions with large proprietary datasets and high-scale computing infrastructure for autonomous vehicle applications.

Requirements

  • Master’s or doctoral degree in Computer Science, Electrical Engineering, or a related discipline.
  • At least three years of industry experience in deep learning and computer vision.
  • Advanced proficiency in Python and PyTorch.
  • Strong capabilities in problem solving, research, and analytical reasoning.
  • Practical experience with generative AI techniques such as diffusion models and GANs.
  • Experience with vision-language models and multimodal learning.
  • Publications at leading conferences such as CVPR, NeurIPS, or ECCV.
  • Hands-on experience with Linux, AWS, Docker, and virtual environments.
  • Knowledge of traditional computer vision methods.

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