Applied AI Researcher – Visual GenAI

Mobileye

. 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.

Posted 9/29/2026full-timeRamat Gan • IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing Generative AI and Computer Vision solutions, leveraging extensive experience in Python and PyTorch. Proven ability to collaborate with cross-functional teams and contribute to cutting-edge research in autonomous driving applications.

Highest-signal resume keywords

Deep LearningComputer VisionGenerative AI MethodsPython ProgrammingPyTorch Framework

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Hard Skills

Deep LearningComputer VisionGenerative AI MethodsPython ProgrammingPyTorch FrameworkVision-Language ModelsMulti-modal LearningAnalytical ThinkingProblem-SolvingResearch Skills

Soft Skills

Strong Problem-SolvingAnalytical Thinking

Tools & Technologies

LinuxAWSDockerVirtual Environments

Certifications & Qualifications

M.Sc. or Ph.D. in Computer ScienceElectrical Engineering

Industry Keywords

Generative ModelsAutonomous DrivingSynthetic DataAI ApplicationsPublications in Top-Tier Conferences

Tech Stack

Tools & technologies

AWSDockerLinuxPythonPyTorch

About the role

Key responsibilities & impact

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.
Develop GenAI solutions using massive proprietary datasets and large-scale computing infrastructure for autonomous vehicle applications.

Requirements

What you’ll need

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.
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.