Senior AI Networking Software Engineer – Scale & Benchmarking

NVIDIA

California (MO)

On-site

USD 184,000 - 287,500

Full time

14 days+

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Job summary

NVIDIA is seeking an AI Networking Software Developer to join our AI Networking SW development and codesign team. You will work on production-ready AI networking frameworks and benchmarks on some of the world’s largest data centers and supercomputers.

You will develop tools that scale across teams, enable new AI models within benchmarking pipelines, and collaborate with networking and hardware teams to optimize performance, automate experiments, and improve end-to-end analytics for complex

Qualifications

  • B.Sc./M.Sc in CS or software engineering, or equivalent experience.
  • At least 5+ years of professional software development experience.
  • Strong Python, Linux and command-line proficiency.
  • Ability to learn across a broad hardware-software stack.

Responsibilities

  • Develop AI networking communication frameworks and production-ready applications for large-scale data centers.
  • Create production tools and benchmarks used by multiple NVIDIA teams.
  • Enable new AI models within benchmarking infrastructure and analyze large-scale workloads across hardware and software stacks.
  • Design and implement automation systems, including large-scale parameter search for optimal configurations.
  • Collaborate with networking and hardware teams to co-design features and interfaces in a fast-paced environment.

Skills

Python
Linux
5+ years experience
Command-line tools
Software development

Education

B.Sc./M.Sc in CS or software engineering

Tools

Slurm
Kubernetes
MPI
InfiniBand

Job description

NVIDIA is seeking an AI Networking Software Developer to join our AI Networking SW development and codesign team. You will work on production-ready AI networking frameworks and benchmarks on some of the world’s largest data centers and supercomputers.

You will develop tools that scale across teams, enable new AI models within benchmarking pipelines, and collaborate with networking and hardware teams to optimize performance, automate experiments, and improve end-to-end analytics for complex

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