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.
Software Development @ 4
Algorithms @ 4
Machine Learning @ 4
Communication @ 4
Debugging @ 4
CUDA @ 4
Deep Learning @ 4
AI @ 4
Computer Vision @ 4
Robotics @ 4
Performance Analysis @ 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 is looking for a Senior Software Performance Engineer to join the Autonomous Vehicles team building end-to-end autonomous driving applications. The role focuses on optimizing latency and throughput for L2/L3/L4 autonomous driving solutions running on NVIDIA multi-computer and heterogeneous hardware architectures.
Responsibilities
- Develop, maintain, and optimize latency and throughput of NVIDIA's L2/L3/L4 autonomous driving solutions.
- Devise acceleration strategies and patterns to improve software architecture and efficiency on systems with multiple heterogeneous hardware engines while meeting product goals.
- Develop highly efficient product code in C++, leveraging algorithmic parallelism via GPGPU programming (CUDA) and ARM NEON, and follow quality and safety standards (e.g., MISRA).
- Collaborate with hardware, product, OS, and safety teams to design next-generation products.
Requirements
- MS or PhD in Computer Science, Computer Architecture, Electrical Engineering, or related field (or equivalent experience).
- 12+ years of relevant professional experience working on autonomous vehicles software.
- Excellent C and C++ programming skills.
- Solid understanding of programming and debugging techniques, especially for parallel architectures.
- Good understanding of system software / operating systems and computer architecture.
- Experience with performance analysis, optimizations, and benchmarking.
- Outstanding communication and collaboration skills; significant interfacing with other teams may be required.
Ways to stand out
- Understanding of embedded architectures and real-time operating systems & scheduling.
- Strong mathematical fundamentals, including linear algebra and numerical methods.
- Experience implementing algorithms in robotics, computer vision, and/or machine learning.
- Software development experience with CUDA / GPGPU or other data-parallel architectures.
- Deep learning architecture / performance work on hardware accelerators, especially GPUs.
Compensation & Benefits
- Base salary ranges provided by level:
- Level 5: 224,000 USD - 356,500 USD
- Level 6: 272,000 USD - 431,250 USD
- Eligible for equity and benefits (link to NVIDIA benefits referenced in original posting).
Additional information
- Applications accepted at least until May 1, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to a diverse work environment.