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# Software Performance Engineer

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, United States
- **Experience:** Expert
- **Salary:** $224,000.0
- **Contract:** Permanent contract
- **Skills:** Computer Vision, C++ (Programming Language), Nvidia CUDA, Computer Programming, Software Debugging, General-Purpose Computing on Graphics Processing Units, Machine Learning, MISRA C (C Programming Language), Software Architecture, Real-Time Operating Systems, Software Engineering, System Software, Graphics Processing Unit (GPU), Deep Learning, Parallel Computation, Information Technology
- **Published:** October 18, 2026
- **Apply:** https://startup.jobs/senior-software-performance-engineer-autonomous-vehicles-2100-nvidia-usa-8997414

## About the Role

* MS or PhD degree 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 as this role might require significant interfacing with other teams within NVIDIA.

Ways to stand out from the crowd:

 * 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 any data parallel architectures.
 * Deep learning architecture/performance work on any HW accelerator, especially if on GPUs.

## Description

* 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 its efficiency on our computers with multiple heterogeneous hardware engines while meeting or exceeding product goals.
 * Develop highly efficient product code in C++, making use of algorithmic parallelism offered by GPGPU programming (CUDA)/ARM NEON while following quality and safety standards such as defined by MISRA.
 * Collaborate with HW, product, OS, and safety teams to design next-gen products.