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Mobileye
Open role>1 month

Applied AI Researcher - Visual GenAI

MobileyeRamat Gan, Israel
Work model
Hybrid
Experience
Not specified
Employment
Full Time
Compensation
Not disclosed
Technology signal
9 tags

Technology context

9

Parsed from the vacancy text; ordered by relevance to this role.

AIAWSGenAIDeep LearningPythonPyTorchComputer VisionDockerLinux

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Role description

Join the group that builds the foundation of Mobileye's perception stack. We are looking for a key member to join our Visual GenAI team, dedicated to advancing state-of-the-art research in visual synthesis and Diffusion Models within a high-impact, real-world AV environment.

You will work on cutting-edge AI research in a real-world environment, backed by massive proprietary datasets and large-scale computing infrastructure. Team up with researchers and engineers from various fields to develop GenAI solutions and develop technology with the potential to impact millions of people and save lives

What will your job look like

  • Own the full development lifecycle: from training generative models to adapting existing state-of-the-art architecture for concrete, real-world autonomous driving use cases.
  • Research, evaluate, and improve GenAI and computer vision models with a focus on scalable and clean Python implementation.
  • Collaborate with cross-functional teams, including AI researchers and perception teams, to integrate synthetic data into real-world AI applications.
  • Stay up to date with the latest advancements in AI, Generative Models, and Computer Vision.

All you need is

  • M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field.
  • 3+ years of industry experience in Deep Learning and Computer Vision.
  • Excellent proficiency in Python and PyTorch.
  • Strong problem-solving, research, and analytical thinking skills.

Advantages

  • Experience with Generative AI methods (Diffusion Models, GANs, etc.).
  • Experience with Vision-Language Models (VLMs) and Multi-modal learning.
  • Publications in top-tier conferences (CVPR, NeurIPS, ECCV, etc.).
  • Experience with Linux, AWS, Docker, and virtual environments.
  • Knowledge of classic computer vision.