Senior Integration Engineer - Autonomous Vehicles

at Nvidia
USD 152,000-287,500 per year
SENIOR
✅ On-site

Used Tools & Technologies

GPU

Required Skills & Competences

Software Development @ 4 Linux @ 4 Algorithms @ 4 Communication @ 7 Git @ 4 Android @ 4 Matlab @ 3 Debugging @ 7 API @ 3 CUDA @ 4 Deep Learning @ 4 AI @ 4

Details

Intelligent machines powered by AI are enabling self-driving cars and robots that can learn, perceive and solve problems. NVIDIA's GPUs run deep learning algorithms used as the brain of computers, robots and autonomous vehicles. This role sits on the team that builds NVIDIA's end-to-end autonomous driving application, working full-stack across heterogeneous hardware and multi-computer architectures to craft self-driving solutions.

Responsibilities

  • Define functional software architecture for NVIDIA's L2/L3/L4 autonomous driving solutions.
  • Integrate modular software components (perception, planning, etc.) to implement customer-required self-driving functions.
  • Optimize product implementation to meet target performance goals and write low-latency, highly performant code.
  • Diagnose system software and functional driving issues on target driving platforms (on-road and simulation).
  • Develop efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines.
  • Perform in-vehicle tests, collect data and complete autonomous drive missions.
  • Develop system tests, document product functions, evaluate quality and propose corrective actions.
  • Develop highly efficient product code in C++, leveraging algorithmic parallelism and GPGPU programming (CUDA).
  • Follow quality and safety standards such as those defined by MISRA.

Requirements

  • 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 (e.g., multimedia systems, game engines) and strong knowledge of programming and debugging techniques.
  • Experience developing software for heterogeneous architectures, including GPUs, and experience with GPGPU programming (CUDA).
  • Knowledge of image processing APIs (e.g., OpenCV) and MATLAB tools; familiarity with automotive systems and ADAS applications.
  • Software development experience on Linux and QNX; solid understanding of Linux, Android, and/or other real-time operating systems.
  • Experience with version control systems (GIT) and build systems such as CMake or Bazel.
  • Hands-on collaborator who works well within teams of algorithm, software and hardware engineers with strong attention to detail and data presentation.

Ways to stand out

  • Understanding of parallel, embedded and distributed architectures.
  • Demonstrated ability to write low-latency, highly performant code.
  • Strong communication and analytical skills; self-motivated and a great teammate.

Compensation & Benefits

  • Base salary ranges (location, experience and level dependent):
    • Level 3: 152,000 USD - 241,500 USD
    • Level 4: 184,000 USD - 287,500 USD
  • Eligible for equity and company benefits.

Other

  • Applications will be accepted at least until March 21, 2026.
  • This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is an equal opportunity employer committed to diversity and inclusion.