Embedded Software Engineer for Architecture Team
About this role
Mobileye is looking for an Embedded Software Engineer for performance verification and profiling.
You will join the Virtual Platforms and Performance Verification team in the EyeQ Platform Group (EPG), working on current and next-generation ADAS/AV systems.
Virtual platforms, performance models, and profiling tools are core components of the EPG infrastructure. These tools are used during the pre-silicon phase for hardware architecture optimization and software development, and in the post-silicon phase for software performance optimization.
\nWhat will your job look like:- Performance verification of EyeQ SoC designs.
- Development of hardware virtual platforms.
- Running hardware benchmarks and correlating virtual platform results with silicon measurements.
- Development of tracing and profiling tools for CPU performance analysis and optimization.
- Close collaboration with hardware architects and software, OS, and algorithm teams.
- BSc/MSc in Computer Science, Computer Engineering, or Electrical Engineering.
- 5+ years of experience in C/C++ programming.
- 5+ years of experience in embedded software development.
- Experience with Python and shell scripting.
- Strong communication and teamwork skills.
- Experience with performance verification.
- Experience with QEMU.
- Experience with CPU benchmarking and performance analysis.
- Experience with Embedded Linux.
- Familiarity with assembly languages and hardware architecture concepts.
- Experience with SystemC.
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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