Deep Learning Algorithm Engineer | Learned-Policy Group

Build the intelligence behind the next driving decision.

We’re developing learning-based driving policies for complex, real-world

scenarios. We’re looking for an engineer who can turn model ideas into reliable

algorithms that run as part of Mobileye’s driving systems.

You’ll work across model development, training, evaluation, and integration.

You’ll analyze model behavior, improve the data and training process, and work

with other teams to validate performance in simulation and on real vehicles.

This is a high-impact role with direct influence on a core part of Mobileye’s

driving technology and its future products.

What will your job look like?

• Develop and improve deep learning models for planning, decision making, and driving behavior.
• Work across the full development cycle, from research papers and prototyping models to building data and evaluation tools, debugging infrastructure, and supporting deployment.
• Design training and evaluation workflows, including metrics for safety, progress, comfort, interaction quality, and robustness.
• Analyze model behavior and failure modes, run experiments, and use the results to improve models and data.
• Collaborate with control, simulation, data, and other algorithm teams to integrate and validate new capabilities.
  
  

• B.Sc. or higher degree in Computer Science, Electrical Engineering, or a related field.
• 3+ years of hands-on industry experience developing and training deep learning models.
• Experience across several stages of the model lifecycle, such as research, model development, data pipelines, evaluation, tooling, integration, and deployment.
• A solid foundation in machine learning, algorithms, and data structures.
• Experience in autonomous driving, robotics, motion planning, prediction, simulation, or control- an advantage
• Familiarity with relevant deep learning fields such as computer vision, generative modeling, reinforcement learning, or multimodal learning- an advantage