As a contractor, you will collaborate with our automotive software team, focusing on the enablement of Neural Processing Unit (NPU) accelerators in MCU and MPU-based platforms. This role is critical to delivering high- performance, AI-enabled automotive applications such as ADAS (Advanced Driver Assistance Systems), sensor fusion, and in-vehicle infotainment. You will work within automotive RTOS or embedded Linux environments, integrating NPU support into existing Board Support Packages (BSPs) and large-scale, safety-critical software stacks.

Your responsibilities

– Develop and integrate low-level software to enable NPU accelerators on automotive-grade MCUs and MPUs.

– Integrate NPU functionality into existing BSPs and complex automotive

software stacks, ensuring compliance with real-time and safety requirements.

– Work within RTOS in automotive such as AUTOSAR and/or embedded Linux environments to support AI/ML workloads.

– Collaborate with hardware, AI/ML, and systems engineering teams to define and optimize accelerator usage,

-Conduct debugging, validation, and performance tuning on target automotive hardware.

– Ensure compliance with automotive safety standards (e.g., ISO 26262) and coding guidelines (e.g., MISRA C/C++).

To ensure your success in this role, the following experience is needed:

Must have skills:

– Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, or related field

– 3–5 years of experience in embedded software development using Embedded C/C++.

– Experience with NPU or AI accelerator integration in embedded systems.

– Proficiency in baremetal/RTOS and/or embedded Linux (e.g., Yocto, Buildroot).

– Experience integrating software into large, layered automotive software stacks.

– Strong understanding of hardware-software interfaces, memory-mapped I/O, and DMA

Any of the following are pluses:

– Experience with AI/ML inference frameworks (e.g., TensorFlow Lite, ONNX Runtime) in embedded automotive contexts.

– Knowledge of functional safety (ISO 26262), ASPICE, and MISRA compliance.

– Exposure to ADAS, sensor fusion, or Audio algorithm with AIML software stacks.

– Familiarity with CI/CD pipelines, version control (Git), and agile development methodologies