Senior Systems Software Engineer - GPU Performance at Scale

at Nvidia

📍 World
📍 Switzerland

PLN 292,500-650,000 per year

SENIOR

✅ Remote

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.

Docker @ 4 Linux @ 4 Python @ 7 Bash @ 7 Communication @ 7 Mathematics @ 8 Networking @ 4 Swift @ 4 CUDA @ 4 GPU @ 4 Deep Learning @ 4 AI @ 4 Slurm @ 4 HPC @ 4

Details

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. This role focuses on GPU Performance at Scale and contributes to world-class computing hardware and software to advance AI workloads. You will provide insights on large-scale system composition and tuning mechanisms for high-performance compute runs and collaborate with researchers, developers, and customers to craft improved workflows and solutions.

Responsibilities

Lead the implementation of performance practices in large-scale GPU infrastructure, delivering 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 and identify root causes.
Collaborate with various software and firmware teams (BMC/SBIOS/OS/drivers, etc.) to develop methods and tools; analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale.

Requirements

Proven understanding of accelerated computing software stacks (CUDA).
Experience with modern cloud and container-based enterprise computing architectures; Slurm preferred.
Strong programming and scripting experience in C/C++, Python, and Bash.
Deep expertise in systems architecture and understanding of how components impact performance.
Experience with container technology and Linux-based OSes; Docker preferred.
Experience supporting high-performance computing or deep learning in engineering or academic research communities.
Strong teamwork and communication skills and results-focused analytical abilities.
BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience); MS or PhD desirable with 10+ 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.

Compensation (as listed in posting)

For Poland: Level 4 base salary range: 292,500 PLN - 507,000 PLN.
For Poland: Level 5 base salary range: 375,000 PLN - 650,000 PLN.

Location & Time Type

Location listed: Switzerland and Remote.
Time type: Full time.