Used Tools & Technologies
GPURequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Linux @ 4
Hiring @ 4
Communication @ 4
Git @ 4
Debugging @ 4
CUDA @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, the company is applying AI to define the next era of computing — with GPUs acting as the brains of computers, robots, and self-driving cars. The team builds NVIDIA's end-to-end autonomous driving application and is seeking engineers who want to work full-stack on multi-computer and heterogeneous hardware architectures.
Responsibilities
- Define functional software architecture for NVIDIA's L2/L3/L4 autonomous driving solutions.
- Integrate modular software components (e.g., perception, planning) to implement customer-required self-driving functions.
- Optimize product implementation to achieve target performance goals.
- Diagnose system software and functional driving issues reported on target driving platforms (on-road and simulation).
- Create 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 high algorithmic parallelism offered by 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 (examples: multimedia systems, game engines) and profound knowledge of programming and debugging techniques.
- Experience developing software for heterogeneous architectures, including GPUs.
- Experience with version control systems (GIT) and build systems such as CMake or Bazel.
- Be hands-on and work well within a team of algorithm, software, and hardware engineers; high attention to detail and strong data organization/presentation skills.
- Solid understanding of Linux and/or other real-time operating systems.
Ways to stand out
- Understanding of parallel, embedded, and distributed architectures.
- Strong ability to write low-latency, highly performant code.
- Excellent communication and analytical skills.
- Self-motivated and a collaborative 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 benefits (link to NVIDIA benefits referenced in original posting).
Other information
- Applications for this job 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 and values diversity in hiring and promotion practices.