Senior Integration Engineer - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking a Senior Integration Engineer to work on their end-to-end autonomous driving application, focusing on integrating modular software components and optimizing performance on heterogeneous hardware architectures. The role involves defining software architecture for L2/L3/L4 autonomous driving solutions, performing in-vehicle and simulation testing, and developing efficient C++ code using CUDA.

What you'd actually do

  1. Defining functional software architecture NVIDIA's L2/L3/L4 autonomous driving solutions.
  2. Integrating modular software components (e.g. perception, planning, etc.) together to implement customer-required self-driving functions.
  3. Optimizing product implementation to achieve target performance goals.
  4. Diagnosing system software & functional driving issues reported on our target driving platforms, including on-road & simulation.
  5. Developing efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines.

Skills

Required

  • PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
  • Excellent C and C++ programming skills.
  • Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc.Profound knowledge of programming and debugging techniques.
  • Experience on developing software in heterogeneous architectures, including GPUs.
  • Knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools, automotive systems, notably ADAS applications.
  • Software development for CUDA, Linux, and QNX.
  • Experience with version control systems GIT and build system like CMake/Bazel.
  • Solid understanding on Linux, Android, and/or other real-time operating systems.

Nice to have

  • Understanding of parallel, embedded and distributed architectures.
  • Thrive on writing low latency, highly performant code.
  • Great communication and analytical skills.
  • Self-motivated and a great teammate.

What the JD emphasized

  • excellent C and C++ programming skills
  • experience developing and debugging multithreaded/distributed applications
  • software development for CUDA, Linux, and QNX
  • knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools, automotive systems, notably ADAS applications

Other signals

  • end-to-end autonomous driving application
  • multi-computer and heterogeneous hardware architectures
  • customer-required self-driving functions
  • on-road & simulation testing
  • GPGPU programming (CUDA)