🕒 5 days ago
Build and operate production machine learning models that personalize the subscriber journey, improve conversion and retention, and support subscription products through scalable, measurable ML capabilities.
Deep Learning Algorithm Engineer - REM Semantics
📅 May 10
Deep LearningPythonPytorchMachine Learning
📜 Description
- Research and develop AI and deep learning algorithms for real-world automotive perception.
- Own projects end to end, from concept and prototyping through model training, evaluation, integration, and scalable deployment.
- Analyze challenging edge cases and improve model performance in complex driving scenarios.
- Collaborate with algorithm developers, software engineers, product managers, and system teams.
- Use large-scale datasets and real-world driving scenarios to improve model accuracy, robustness, and runtime efficiency.
- Bring ideas into production-ready systems for autonomous vehicle technologies.
🛠️ Requirements
- B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance.
- 3+ years of hands-on experience developing deep learning solutions using Python and frameworks such as PyTorch.
- Strong foundation in algorithms, machine learning, and deep learning fundamentals.
- Strong analytical skills, ownership, and ability to collaborate.
- Computer vision or graph neural network experience is an advantage.
- Experience with AI agents and modern development productivity tools is a plus.
- Experience with cloud environments and big data tools is a plus.
Full job description
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:
-
Conduct hands-on research and development of AI and Deep Learning algorithms for real-world automotive perception tasks.
-
Own projects end-to-end — from concept, through research, prototyping, designing, training, and evaluating neural network architectures, to integration and scalable deployment.
-
Analyze challenging edge cases and continuously improve model performance in complex driving scenarios.
-
Collaborate with algorithm developers, software engineers, product managers and system teams across the organization.
-
Work with large-scale datasets and real-world driving scenarios to improve model accuracy, robustness, and runtime efficiency.
-
Bring your ideas into production-ready systems that have a direct, measurable impact on autonomous vehicle technologies used worldwide.
All you need is:
-
B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance.
-
3+ years of hands-on experience developing deep learning solutions using Python and frameworks such as PyTorch.
-
Solid foundation in Algorithms, Machine Learning, and Deep Learning fundamentals (Computer Vision / Graph Neural Networks – advantage).
-
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.
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