ML Software & Infrastructure Engineer (Student Position)
About this role
Mobileye’s Hawkeye team is developing advanced close-range 3D perception for autonomous vehicles, enabling safe automated parking and low-speed maneuvers in tight environments. We build multi-camera deep learning systems for precise and reliable understanding of the vehicle’s surroundings.
In this role, you will build the software and infrastructure that bridges our algorithmic research with real-world production. You will be responsible for making sure our models run efficiently at scale and on the vehicle's hardware.
\nWhat will your job look like:• Develop and maintain critical ML infrastructure to accelerate the research team's workflow.
• Build and manage robust data processing pipelines (ETLs) for large-scale autonomous driving datasets.
• Create performance analysis tools and optimize deep learning training processes.
- Currently pursuing a B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related field from a leading university with high achievements.
- Availability to work at least 3 days per week.
- Strong hands-on programming skills in both C++ and Python.
- Solid foundation in software engineering principles, data structures, and algorithms.
- Highly motivated, proactive, and capable of taking ownership of software projects in a fast-paced R&D environment.
Advantages:
- Experience working in Linux environments and utilizing tools like Git and Docker.
- Familiarity with deep learning frameworks (e.g., PyTorch) and an understanding of how ML training pipelines operate under the hood.
- Prior experience with data engineering, ETL pipelines, or database management.
- Background in code optimization, embedded systems, or hardware-aware programming.
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!
Company at a glance
Mobileye pioneers physical AI for intelligent systems including advanced ADAS, autonomous driving solutions, and humanoid robotics.
Mobileye’s physical AI foundation reflects decades of experience in real-world driving intelligence, applying the same engineering principles that shaped its automotive AI leadership to AI for humanoid robotics in complex physical environments.
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