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# Senior Systems Software Engineer - GPU Performance at Scale

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Systems Engineering, Bash Shell, C++ (Programming Language), Cloud Engineering, Nvidia CUDA, Computer Programming, Software Debugging, Linux, Microprocessors, Firmware, Systems Analysis, Networking Hardware, Python (Programming Language), Software Engineering, Systems Architecture, Graphics Processing Unit (GPU), Cloud Platform System, High Performance Computing, Deep Learning, Computer Equipment, Containerization, Information Technology, Slurm, Hardware Infrastructure, Docker
- **Published:** November 6, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-systems-software-engineer-gpu-performance-at-scale-santa-clara-ca--a4a5a009-792c-4e5e-9767-7b2c23fff1f6

## About the Role

Software Engineering, GPU (Graphics Processing Unit), Systems Engineering, Autonomous Driving Systems, GPU (Graphics Processing Unit), Artificial Intelligence (AI), Operating Systems, Large-Scale Systems, Software Engineering, Computer Hardware, * Proven understanding of accelerated computing software stacks (CUDA).

 * Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred.
 * Strong programming and scripting experience in C/C++/Python/Bash.
 * Deep expertise in systems architecture and the impact of various components on performance.
 * Experience with container technology and Linux-based OSes, with Docker preferred.
 * Experience supporting high-performance computing or deep learning in engineering or academic research communities.
 * Strong teamwork and communication skills, coupled with results-focused analytical abilities.
 * BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience); MS or PhD desirable with 8+ years of applicable experience.

Ways to Stand Out From the Crowd

 * End-to-end GPU performance engineering from the profiler to systems analysis.
 * Linux systems programming and optimization experience.
 * Exposure to virtualization techniques and cloud platform solutions.
 * Experience with scheduling and resource management systems.
 * Experience with large-scale HPC environments.

## Description

* Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently.
 * Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware. Engage early with HW/FW/SW/platform internal and customer teams.
 * Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions.
 * Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause.
 * Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools. Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale.