Identify, analyze, design, develop and debug system software for Camera/Imaging and Computer Vision features on Linux, QNX Android systems.
Deliver quality code, debug complex problems, prioritize and get things done with a high level of efficiency and urgency.
Collaborate with cross-functional teams across multiple engineering and algorithms teams, making the architectural, design tradeoffs required to deliver scalable end to end software stack across various compute engines.
Stay open-minded, constantly dive into innovative technologies, and embrace the ambiguity of complex problem solving.
Qualifications
Hands-on experience with C/C++ on Linux and/or RTOS based systems.
Master's Degree in Electronics, Computer Engineering or Computer Science.
Exceptional candidates with Bachelor's degree in Computer Science and relevant work experience will also be considered.
Experience with optimizing code across various compute engines and heterogeneous computing ( CPU / GPU / DSP / etc)
Experience with best in class Engineering practices, technical documentation, design/architecting, and code reviews.
Experience with software update strategy for development and mass production phases including but not limited to OTA SW updates, factory SW updates, recovery SW updates, secure SW updates, etc.
Experience with one or more HAL architectures (preferably Camera HAL)
Familiarity with HW bring up, MIPI / CSI drivers, V4L2 drivers, SerDes drivers would be a positive.
Good understanding and hands on experience with interface protocol stacks (SPI,I2C, Ethernet).
Deep understanding of the camera processing pipeline from a systems level, including ISP, sensors, SerDes, power management, etc.
Familiar with RTOS kernel (Threadx or QNX), IPC, kernel and user space driver model.
Preferred Qualifications:
PhD in EE/Computer Science with relevant emphasis in image processing, graphics and/or Artificial Intelligence
Experience with automotive surround view systems/use cases along with their optimized implementation on GPUs using OpenGL/Vulkan/OpenCL APIs.
Background in the automotive industry or experience with safety-critical systems.
Experience with AI SDKs and building systems on edge devices
Track record of innovative thinking as evidenced by patents and peer-reviewed Publications.