Senior Systems Software Engineer - Holoscan Sensor Bridge

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Systems Engineer role focused on building and optimizing high-speed sensor streaming applications on NVIDIA's Holoscan platform, involving GPUs, networking, and embedded systems. Requires strong C/C++/Python skills and experience with Linux kernel, networking stack, and hardware acceleration.

What you'd actually do

  1. Build applications and features for the Holoscan platform centered around GPUs, high bandwidth network acceleration SDKs, cameras, and sensors.
  2. Architect, build, develop, and benchmark innovative, scalable, and performant hardware-accelerated software and high bandwidth sensor streaming systems on NVIDIA’s Holoscan platform and GPUs.
  3. Perform and participate in code reviews and build reviews to ensure the highest quality standards.
  4. Engage with strategic customers, partners, and internal NVIDIA teams to train, compose, build, and productize solutions based on the Holoscan/Hololink platforms.
  5. Provide technical mentorship and direction to other developers in the group, encouraging a cohesive and collaborative environment.

Skills

Required

  • Linux Kernel
  • Linux Networking stack
  • RTOS concepts
  • embedded systems
  • Remote Direct Memory Access (RDMA)
  • GPU/CUDA concepts
  • C/C++/Python
  • Linux distros (Ubuntu, L4T)
  • Yocto
  • Bachelor’s, Master’s, or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related science degree (or equivalent experience)

Nice to have

  • GPU/CUDA programming
  • Software-Defined Networking (SDN)
  • DPUs
  • SmartNICs
  • NIC drivers
  • cameras
  • sensors
  • system performance analysis
  • low-level programming
  • RoCE/DPDK/DOCA/Rivermax
  • Holoscan SDK development

What the JD emphasized

  • 8+ years of solid hands-on experience writing code in C/C++/Python
  • Knowledge of Linux Kernel, Linux Networking stack, and RTOS concepts and considerations.
  • Deep understanding of embedded systems, Remote Direct Memory Access (RDMA), and GPU/CUDA concepts.