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NVIDIA

Designs the chips and software that power AI

System Software Engineer - Infrastructure

Platform EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A BS or MS degree in Electrical Engineering, Computer Science, or Computer Engineering, or equivalent experience, and at least 5 years of software, infrastructure, DevOps, or site reliability engineering experience.
  • Hands-on experience with modern continuous integration/continuous delivery and test automation, including architecting and debugging pipelines and working with test orchestration frameworks such as pytest or equivalent.
  • Experience or demonstrated curiosity in device BIOS, firmware, or other low-level embedded software, and interest in building tooling for its engineers.
  • Understanding of web services, REST APIs, relational databases, and schema design, including SQL and PostgreSQL.
  • Scalability thinking.
  • Strong Python skills and comfort working in Linux shell environments.
  • Ability to articulate questions, write clear requirements, review critically, and explain trade-offs.
  • Interpersonal skills, empathy, and curiosity to work closely with hardware and software engineers on process and tooling enhancements.

Responsibilities

  • Build, supervise, and improve core infrastructure for firmware teams, including build systems, regression farms, continuous integration/continuous delivery pipelines, developer tooling, and supporting frameworks and web services.
  • Debug and resolve issues across hardware, software, infrastructure, and team processes, addressing the broader class of issue where possible.
  • Invent and build AI-powered workflows that scale individual, team, or company output.
  • Learn, document, and automate processes, services, and tooling for internal- and external-facing projects.
  • Identify and eliminate company-wide toil, developing improvement ideas from proof of concept through fully shipped, scalable solutions.

Desired Qualifications

  • Experience with containers, orchestration, or infrastructure-as-code tooling such as Kubernetes.
  • Experience using AI-assisted development tools, including assessing trustworthiness and when to validate or discard their output.
  • A side project, open-source contribution, or internal tool built to address an annoyance or inefficiency.
  • A track record of writing clear technical proposals, design documents, or architecture decisions that others have acted on independently.

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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