Level

NVIDIAPosted 2d ago

Senior Software Developer, AI Networking

Senior Software Developer, AI Networking at NVIDIA scores 85 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Switzerland, ZurichseniorFull time

AI in this role

Develops AI networking communication frameworks, benchmarking infrastructure, and performance optimization tools for large-scale data centers.

pytorchpythonlinuxslurmkubernetesmpiinfiband
ai-networkingbenchmarkingautomationperformance-optimization

NVIDIA is changing the world of AI Networking with groundbreaking technology. We are excited to be adding an AI Networking Software Developer to our AI Networking SW development and codesign team. We are working with the latest NVIDIA hardware and technologies. We do full stack benchmarking for Data Center scale systems for AI training/inference and lower level benchmarks. We strive for automation and develop many tools in-house yet adopt community accepted practices and frameworks. Moreover we give back to community developing our own tools in public GitHub repositories. Our goal is to ensure that large-scale systems deliver expected performance in practice, not just on paper, by uncovering bottlenecks and driving continuous improvements.


What you'll be doing:

  • Developing AI networking communication frameworks and applications running in production on the world’s largest supercomputers and data centers.
  • Develop production tools and benchmarks used by multiple teams inside and outside NVIDIA.
  • Enable new AI models within our benchmarking infrastructure and deliver insights through end-to-end analysis of large-scale workloads across hardware and software stacks.
  • Design and implement automation systems, including large-scale parameter search to identify optimal configurations across complex systems.
  • Collaborate closely with networking and hardware teams to co-design new features and software interfaces in a fast-paced, evolving environment.

What we need to see:

  • B.Sc., M.Sc degree in Computer Science / Software engineering, and 12+ years or equivalent experience.
  • Professional Python development experience. We seek individuals who build maintainable, long-lived tools that do not impose a heavy burden on the team in terms of maintenance.
  • Solid Linux expertise and passion for working extensively in command-line environments.
  • Ability to work across a broad and evolving stack, with a strong drive to learn—from hardware and networking up to large-scale AI systems running across entire clusters

Ways to stand out from the crowd:

  • Knowledge and/or experience with modern AI ecosystem: PyTorch, LLMs, inference and training.
  • Familiarity with cluster orchestration systems such as Slurm or Kubernetes.
  • Knowledge in MPI and HPC, InfiniBand, Ethernet and Networking.
  • Experience in performance optimizations

For two decades, we have pioneered visual computing, and the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning. This new model - where deep neural networks are trained to recognize patterns from massive amounts of data - has shown to be deeply effective at solving some of the most complex problems in everyday life. NVIDIA is widely considered to be one of the technology world's most desirable companies to work for. Are you creative and driven? Do you love a challenge? If so, we want to hear from you.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI NetworkingBenchmarkingAutomationPerformance OptimizationPyTorchPythonLinuxSlurm

Questions you could be asked

  1. Tell me about a project where ai networking was part of your work. What did you do?
  2. Tell me about a project where benchmarking was part of your work. What did you do?
  3. Tell me about a project where automation was part of your work. What did you do?
  4. Tell me about a project where performance optimization was part of your work. What did you do?
  5. Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: AI Networking, Benchmarking, Automation, Performance Optimization, and PyTorch. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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