Senior/Staff Software Engineer, Runtime

Responsibilities:

• Work closely with our autonomy and runtime teams to improve our redundant on-vehicle platform and autonomous software stack.
• Develop perspectives on where opportunities and gaps might be in our redundant software and hardware strategy with a longer-term horizon in mind
• Integrate and optimize performance and robustness of different autonomous software component into redundant on-vehicle platform.
• Design and develop fault detection and fault handling strategies for redundant on-vehicle platform.
• Design and develop validation strategies for redundant on-vehicle platform, including on vehicle testing, Sil and HiL simulation testing.
• Evaluate, integrate and optimize partner middleware into our AD stackOwns or help with driverless operation key features, like mission control, tele assist, etc.
• Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
• Ensure team compliance with QMS, monitor quality, and drive process improvements.

Required Skills:

• Minimum 5+ years of professional experience
•  MS or PhD in Computer Science or related field
• Strong programming skills in C++ and Python
• Basic understanding of computer vision and deep learning models
• Hands-on experience of high performance IPC / middleware stack
• Strong analytical skills, especially for performance troubleshooting (e.g. profiling, roofline model)
• Familiarity with CUDA, OpenCL, OpenVX, Halide or other SIMD programming models.
• Ability to quickly learn and adapt to new technology
• Ability to work on large code bases and a fast growing environment
• Strong communication skills
• Familiar with Linux system and basic kernel tuning, network tuning, device tree tuning, timesync, etc.
• Comfortable with On-vehicle troubleshooting and performance profiling

Preferred Skills

• Experience with CV pipeline and model inference on edge platforms
• Experience with ROS2 and DDS
• Experience with automotive HPC SoCs (Nvidia preferred)
• Experience with QNX

Responsibilities:

• Work closely with our autonomy and runtime teams to improve our redundant on-vehicle platform and autonomous software stack.
• Develop perspectives on where opportunities and gaps might be in our redundant software and hardware strategy with a longer-term horizon in mind
• Integrate and optimize performance and robustness of different autonomous software component into redundant on-vehicle platform.
• Design and develop fault detection and fault handling strategies for redundant on-vehicle platform.
• Design and develop validation strategies for redundant on-vehicle platform, including on vehicle testing, Sil and HiL simulation testing.
• Evaluate, integrate and optimize partner middleware into our AD stackOwns or help with driverless operation key features, like mission control, tele assist, etc.
• Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
• Ensure team compliance with QMS, monitor quality, and drive process improvements.

Required Skills:

• Minimum 5+ years of professional experience
•  MS or PhD in Computer Science or related field
• Strong programming skills in C++ and Python
• Basic understanding of computer vision and deep learning models
• Hands-on experience of high performance IPC / middleware stack
• Strong analytical skills, especially for performance troubleshooting (e.g. profiling, roofline model)
• Familiarity with CUDA, OpenCL, OpenVX, Halide or other SIMD programming models.
• Ability to quickly learn and adapt to new technology
• Ability to work on large code bases and a fast growing environment
• Strong communication skills
• Familiar with Linux system and basic kernel tuning, network tuning, device tree tuning, timesync, etc.
• Comfortable with On-vehicle troubleshooting and performance profiling

Preferred Skills

• Experience with CV pipeline and model inference on edge platforms
• Experience with ROS2 and DDS
• Experience with automotive HPC SoCs (Nvidia preferred)
• Experience with QNX

AI-powered autonomous driving for a safer, greener world.