Deep Learning Algorithm Engineer - REM Semantics
You will be part of Mobileye's REM (Road Experience Management) department which is responsible for the automatic High Definition map-making process, which is a key technology in Mobileye's autonomous driving and high-end Driving Assistance systems.
You will be joining the team that builds the state-of-the-art AI-powered relevancy systems at scale. You will be designing and implementing semantic understanding engines that power data-driven products across autonomous driving and beyond, combining cutting-edge Computer Vision, Graph Neural Networks, and efficient inference to solve real-world perception challenges.
What will your job look like:
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Conduct hands-on research and development of AI and Deep Learning algorithms for real-world automotive perception tasks.
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Own projects end-to-end — from concept, through research, prototyping, designing, training, and evaluating neural network architectures, to integration and scalable deployment.
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Analyze challenging edge cases and continuously improve model performance in complex driving scenarios.
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Collaborate with algorithm developers, software engineers, product managers and system teams across the organization.
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Work with large-scale datasets and real-world driving scenarios to improve model accuracy, robustness, and runtime efficiency.
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Bring your ideas into production-ready systems that have a direct, measurable impact on autonomous vehicle technologies used worldwide.
All you need is:
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B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance.
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3+ years of hands-on experience developing deep learning solutions using Python and frameworks such as PyTorch.
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Solid foundation in Algorithms, Machine Learning, and Deep Learning fundamentals (Computer Vision / Graph Neural Networks – advantage).
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Strong analytical skills, a sense of ownership, and the ability to work collaboratively.
Nice to have:
- Experience leveraging AI agents and modern productivity tools in development workflows.
- Experience with cloud environments and big data tools.