You'll join Mobileye's REM (Road Experience Management) department. REM is an end-to-end mapping and localization engine that supports full autonomy capabilities and services.
Building validation processes and methods for a technology of this scale is challenging, meaningful and rewarding work. The system is complex and based on machine learning and image processing, so analysis and validation take deep thinking and strong technical and analytical skills. You'll develop validation infrastructure, tools and methods using cutting-edge technology and cloud-based applications. We use AI wherever it helps: to automate routine work, improve code quality and make our development process more efficient.
What your job will look like:
- Plan and build advanced, end-to-end validation processes for REM mapping and localization.
- Build validation tools that use geometric calculations, logic and heuristics.
- Add new features to the validation pipeline and make it more sensitive, faster and better.
- Use AI tools to improve the development process, for example automated code review, unit-test generation and automating repetitive tasks.
- Work with algorithms and tools from other R&D groups and build them into the validation infrastructure.
- Analyze large-scale data on the cloud and turn the results into clear conclusions.
All you need is:
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B.Sc. in Computer Science, Software Engineering or a related field.
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3+ years of hands-on software development, with Python in production (Pandas, NumPy, SciPy, etc.).
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Good coding practice: Git, testing, CI/CD.
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Daily, hands-on use of AI coding assistants and agents (e.g., GitHub Copilot, Claude Code, Cursor).
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A critical eye for AI output: reviewing, testing and checking AI-generated code and results.
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Strong analytical skills, with broad vision and technical depth.
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Good communication and teamwork across groups.
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Fluent English.
Nice to have:
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Experience automating development and data workflows with LLM-based tools and agents.
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Knowledge of descriptive statistics, probability and statistical inference.
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Geometry or geospatial work (Shapely, GeoPandas, coordinate systems).
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Cloud and distributed processing (AWS S3/Athena, SQL, Spark/PySpark).
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Computer vision, ML or mapping/localization.