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NVIDIA

Designs the chips and software that power AI

Senior Software Engineer - Distributed Systems Engineering

Platform EngineeringUpdated on Nov 13
Full-timeRemote

About the Job

Requirements

  • Direct experience in a software engineering role within a highly technical organization, with demonstrable impact from prior work.
  • Software development experience with Kubernetes APIs and frameworks, not merely operating a cluster.
  • At least 8 years in a similar role and experience with large-scale production systems.
  • Knowledge of common software engineering principles, tools, and techniques.
  • A BS in Computer Science, Engineering, Physics, Mathematics, or a comparable degree, or equivalent experience.
  • Knowledge of a systems programming language such as Go or Python, and a solid understanding of data structures and algorithms.

Responsibilities

  • Work on the DGX Cloud team responsible for production systems that enable large-scale GPU clusters to support various AI workloads, including custom software for scheduling GPU resources on Kubernetes.
  • Implement monitoring and health-management capabilities for reliability, availability, and scalability of GPU assets, using data streams from GPU hardware diagnostics, cluster telemetry, and network telemetry.
  • Work with teams across NVIDIA to ensure production AI clusters run reliably and consistently at maximum performance.
  • Evaluate system failures and improve services through a well-defined incident-management process.

Desired Qualifications

  • Technical competency in managing and automating large-scale distributed systems independent of cloud providers.
  • Advanced hands-on experience and deep understanding of cluster-management systems such as Kubernetes, Slurm, and Bright Cluster Manager.
  • Proven operational excellence in maintaining reliable and performant AI infrastructure.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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