Mobileye
Radar System Integration Engineer – Functional & System Flows
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Petah Tikva, Israel
Work mode:
Onsite
Published on:
19 August 2026
What they need
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 with Linux environments and shell scripting.
- Strong analytical, root-cause investigation, and problem-solving skills across combined SW/HW layers.
- Team player, proactive, self-motivated, with a strong sense of ownership and quality.
- Experience with Automotive Cybersecurity standards and mechanisms (ISO/SAE 21434, Secure Boot, HSM integration, MACsec/SecOC) - Advantage
- Familiarity with CI/CD integration pipelines (GitLab CI, Jenkins) and automated test frameworks (PyTest) - Advantage
- Experience with 4D Imaging Radar or other ADAS sensors (LiDAR, Camera) - Advantage
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