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Location
Hybrid (Petah Tikva, Israel)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 12, 2026. First seen by Alion on Aug 19, 2026.

Overview
Company
Impact
Profile match
Mobileye is an Israeli company founded in Jerusalem in 1999 by the computer scientist Amnon Shashua and the entrepreneur Ziv Aviram, built on the then-contrarian idea that a single camera and clever software could handle driver assistance without radar or lidar. Its EyeQ system-on-chip has shipped in more than two hundred million vehicles, making it the dominant supplier of vision-based driver assistance to the global car industry. Acquired by Intel for fifteen billion dollars in 2017 and returned to public markets in 2022, the company now sells escalating tiers from basic assistance through the SuperVision and Chauffeur hands-off systems up to the fully driverless Mobileye Drive platform.

Our vision is to bring new and cutting-edge automotive radar sensor solutions, while leveraging our core assets and expertise in this field. Introducing cutting-edge, best-in-class sensors that complement end-to-end autonomous driving solution platforms.

You will be joining an excellent group of people working on advanced mmWave Imaging Radar technology in a dynamic and challenging environment. This role requires close collaboration with System Architecture, Embedded Software, Security, Algorithm, and Hardware teams to define, integrate, and validate the radar’s operational behavior and system-level flows.

The job includes designing functional test environments, developing automated end-to-end validation pipelines, debugging complex SW/HW interactions, verifying system state machines, analyzing functional KPIs, ensuring compliance with automotive cybersecurity standards, and leveraging state-of-the-art AI-assisted development tools to drive scalable engineering velocity.

What will your job look like:

    • Lead radar functional integration from system requirements through the complete development lifecycle to client deployment.
    • Define, design, and execute end-to-end Integration Test Plans (ITP) focused on system state machines, boot/initialization sequences, operational modes, and error-handling mechanisms.
    • Characterize, analyze, and optimize critical functional KPIs, including end-to-end data latency, frame timing jitter, frame drop rates, and throughput bottlenecks.
    • Integrate and validate Radar security features
    • Design and implement scalable automated test benches and automated test suites using Python.
    • Leverage AI-assisted development workflows and agentic tools (Cursor, Claude Code, GitHub Copilot) to accelerate integration design, automation generation, logs analysis, and rapid test suite scaling.
    • Perform deep-dive root-cause analysis on multi-disciplinary system bugs, software crashes, bus communication anomalies, and unexpected mode transitions.
    • Provide continuous functional feedback to SW, System, and Security architecture teams during early development phases.
    • Deliver comprehensive integration status reports and test coverage dashboards.
    • Provide direct technical support to key automotive customers and tier-1 partners on complex functional integration issues.

All you need is:

    • B.Sc. in Electrical Engineering, Computer Engineering, Software Engineering, Communication Systems, or equivalent.
    • 3+ years of hands-on experience in multi-disciplinary System Integration, Embedded Software Integration, or System Validation (Automotive or Defense/Aerospace preferred).
    • Deep understanding of System Functional Architecture: State machines, OS/RTOS fundamentals, inter-process communication, and embedded SW/HW interaction.
    • Proven experience measuring and debugging Functional KPIs (for example: timing jitter, latency breakdown, packet/frame drops, CPU/bus load).
    • Solid programming and scripting skills in Python (for automation frameworks, data parsing, and test scripting).
    • Active practitioner in modern AI-assisted engineering: Proven proficiency in using AI tools and LLM interfaces (e.g., Cursor, Claude Code, GitHub Copilot) for day-to-day coding, scalable test automation generation, and rapid log debugging.
    • Hands-on experience withLinux environments and shell scripting.
    • Strong analytical, root-cause investigation, and problem-solving skills across combined SW/HW layers.

Nice to have:

    • Experience with Automotive Cybersecurity standards and mechanisms (ISO/SAE 21434, Secure Boot, HSM integration, MACsec/SecOC).
    • Familiarity with CI/CD integration pipelines (GitLab CI, Jenkins) and automated test frameworks (PyTest).
    • Experience with 4D Imaging Radar or other ADAS sensors (LiDAR, Camera).
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