ML Software & Infrastructure Engineer – Student Position

Mobileye

ML Software Engineer in Mobileye's Hawkeye team developing software for autonomous vehicle perception. Involves building infrastructure linking research with production for safe automotive systems.

Posted 7/28/2026full-timeRamat Gan • 🇮🇱 IsraelEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong programming skills in C++ and Python, with a solid foundation in software engineering principles, data structures, and algorithms. Capable of developing and maintaining machine learning infrastructure and data processing pipelines in a fast-paced research and development environment.

Highest-signal resume keywords

C++ ProgrammingPython ProgrammingMachine Learning InfrastructureData Processing PipelinesSoftware Engineering Principles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C++PythonData StructuresAlgorithmsMachine LearningETLPerformance AnalysisDeep Learning OptimizationSoftware DevelopmentData Processing

Soft Skills

Highly MotivatedProactiveOwnershipFast-Paced Adaptability

Industry Keywords

Autonomous DrivingR&D EnvironmentMobileye

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Implement, optimize, and maintain post-processing code that runs directly on Mobileye's target chips (primarily in C++).
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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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.