Reinforcement Learning Researcher | Learned-Policy Group
Jerusalem, Israel
R&D – Algorithms /
Full time /
Hybrid
Build the intelligence behind the next driving decision.
We’re building a reinforcement-learning driving planner for complex,
interactive road scenarios. We’re looking for a researcher to help take it from
simulation to real vehicles.
You’ll develop policy models, rewards, and training methods. You’ll define how
driving behavior is evaluated, analyze failures in closed loop, and validate
improvements on the road. You’ll work in a small team at Mobileye and
collaborate with control and other algorithm teams.
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?
- Research and develop reinforcement-learning planning algorithms, including
policy architectures, reward design, training objectives, and optimization
methods. - Train and evaluate RL policies for difficult, interactive driving scenarios,
building on the existing learning-based planner and complementary classical
components. - Develop evaluation methods and relevant metrics for safety, progress, comfort,
and interaction quality, and use them to guide experiments and analyze
failures. - Build simulation-based training and closed-loop evaluation workflows.
- Turn research ideas into reliable components of the driving stack.
All you need is:
- M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related
field. - 3+ years of hands-on industry experience in deep learning, including designing
and training neural networks. - Hands-on reinforcement-learning experience through research or practical
application. - Experience in autonomous driving, robotics, motion planning, simulation, or
closed-loop evaluation- an advantage
Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
