Embedded Software Engineer

7 days ago

Palo Alto, United States Satyam Venture Engineering Services Full time

JOB DESCRIPTION

This role is hybrid- 2 times per week.

Schedule: M-F


Job duration : Jan 1, 2025 - Dec 31, 2025


Responsibilities:

  • 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, and 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.

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