Staff System Software Engineer

Job Title

Staff System Software Engineer

Role Summary

Senior engineer on the system software team responsible for developing and integrating low-level software for Ambarella AI vision processor platforms. The role focuses on platform bring-up, OS/kernel work, device drivers, performance and power optimization, and cross-team delivery for embedded vision products.

Experience Level

Senior (Staff-level). Years-of-experience guidance not specified in the source.

Responsibilities

Typical responsibilities include:

• Design, implement, and maintain low-level system software (bootloader, kernel, drivers, platform BSPs).
• Bring up SoC platforms and integrate firmware, device drivers, and OS components.
• Profile and optimize performance and power on embedded vision processors.
• Debug and resolve hardware/software integration issues on target hardware.
• Collaborate with hardware, firmware, algorithm, and QA teams to deliver production releases.

Requirements

Must-have and preferred technical skills:

• Must-have: Strong proficiency in C/C++ and low-level programming for embedded systems; experience with Linux kernel and device driver development; familiarity with cross-compilation toolchains and embedded build systems; experience in platform bring-up and hardware debugging.
• Must-have: Practical experience using debugging tools, trace tools, and hardware interfaces (JTAG, UART, etc.).
• Nice-to-have: Experience with video codecs, multimedia pipelines, computer-vision workloads, RTOS, or firmware development; scripting for automation and test.

Education Requirements

Not specified.

About the Company

Company: Ambarella

Headquarters: Santa Clara, California, USA

Ambarella is a leader in computer vision and video processing technology, providing advanced solutions that enhance the performance of video applications. Focused on quality and innovation, Ambarella develops products for diverse uses, including autonomous vehicles, surveillance systems, and smart cameras, aiming to deliver pristine imagery and efficient compression while minimizing power consumption.