Used Tools & Technologies
Not specified
Required 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.
Software Development @ 4
Linux @ 4
Communication @ 7
Git @ 4
Android @ 4
Debugging @ 7
CUDA @ 4
AI @ 4
OpenGL @ 4
OpenCL @ 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
The Autonomous Vehicles Platform team builds the NVIDIA DriveWorks SDK to provide a scalable software stack and framework to build autonomous vehicles. The team develops core technology around sensor drivers and interfaces, data streaming, data recording and playback, and vehicle interface abstraction.
Responsibilities
- Create and optimize software architecture and frameworks for real-world performance while matching or exceeding customer requirements.
- Work with vendors developing innovative sensors for vehicles.
- Develop sensor drivers, plug-ins, and processing functions around sensor data.
- Create highly efficient sensor data recording, playback and visualization tools.
- Perform in-vehicle tests, collect data and analyze integrity.
- Work with car teams and control teams to develop interfaces to vehicles to enable self-driving.
- Support data collection campaigns for the autonomous vehicle program.
- Develop unit tests and documentation for features, evaluate quality and propose corrective actions.
- Create highly efficient product code in C++, leverage high algorithmic parallelism offered by GPGPU programming (CUDA), and follow quality and safety standards such as MISRA.
Requirements
- BS/MS in Computer Engineering, Computer Science or related field (or equivalent experience).
- Excellent C and C++ programming skills.
- 8+ years of proven experience developing and debugging multithreaded/distributed applications (e.g., multimedia systems, game engines).
- Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures.
- Background on Linux, Android, and/or other real-time operating systems.
- Experience with sensors such as cameras, LiDAR, radar, ultrasonics, IMU, GPS.
- Experience with vehicle control interfaces.
- Ability to write low latency, highly performant code.
- Strong communication and analytical skills.
Ways to Stand Out
- Understanding of embedded architectures.
- Experience with data-parallel and/or GPGPU programming, CUDA, and OpenCL.
- Software development for modern OpenGL (Core Profile) and Linux.
- Experience with version control systems (GIT) and build system CMake.
Compensation & Benefits
- Base salary ranges by level provided: Level 4 — 184,000 USD to 287,500 USD; Level 5 — 224,000 USD to 356,500 USD.
- Eligible for equity and benefits (link provided in original posting).
Other Details
- Location: Santa Clara, CA, United States.
- Employment type: Full time.
- Applications accepted at least until May 1, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to diversity and inclusion.