C++ Engineer Automotive Embedded System IRC265429

Description

We are seeking an experienced Performance Optimization Engineer with deep expertise in Android Automotive, Linux kernel, and QNX environments. This role focuses on system-level analysis and performance tuning across embedded automotive platforms. The ideal candidate brings hands-on experience with low-level diagnostics, kernel-level performance tracing, and deep familiarity with embedded software development in Java, C, and C++, with additional scripting using Python.

This position involves direct collaboration with internal engineering teams and external technology partners such as Google and QNX, with a shared goal of optimizing end-to-end system performance, traceability, and responsiveness in automotive head units and ECUs.

Requirements

Must-Have skills:

• Proven experience in Android Automotive platform development.
• Deep understanding of Linux kernel performance mechanisms, QNX, and embedded system fundamentals.
• Strong programming skills in Java (Core), C, C++, with scripting experience in Python.
• Hands-on experience with system tracing tools like Systrace, ftrace, and Perfetto.
• Experience with automated testing, profiling, and debugging embedded systems at scale.
• Familiarity with performance benchmarking, log analysis, and fault injection techniques.
• Excellent problem-solving skills, with a systems-thinking approach to diagnostics and tuning.

Nice-to-Have:

• Experience with Android HAL, AOSP, or OEM-specific automotive stacks.
• Familiarity with Google Automotive Services (GAS) or xTS certification (CTS, VTS, etc.).
• Prior collaboration with chip vendors or Tier-1 suppliers.
• Experience with CI/CD environments, test infrastructure, and Jenkins pipelines.
• Understanding of power management, startup time optimization, and latency tuning.

Job responsibilities

• Analyze and debug system-level performance issues using logs, manual tests, and field fault reports.
• Perform root cause analysis and implement performance improvements via code changes or system configuration updates.
• Use advanced tracing tools (Systrace, ftrace, Perfetto) to identify bottlenecks across the Android stack, Linux kernel, and QNX.
• Develop and maintain automated performance tests and integrate them into CI/CD pipelines.
• Design, implement, and improve custom performance measurement tools to track metrics like boot time, memory usage, CPU load, and rendering latency.
• Collaborate with partner organizations (e.g., Google, QNX) on benchmarking, certification, and compliance testing.
• Document performance guidelines, thresholds, and remediation best practices for use by other teams.
• Contribute to architectural decisions that improve system performance and scalability.