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NVIDIA

Designs the chips and software that power AI

Applied Systems Engineering Rotation Engineer New Grad

DevOps & InfrastructureConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree or master's degree, or equivalent experience, in Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Data Science, Mathematics, Physics, or a related technical field.
  • Experience with software development or scripting in Linux, Bash, Python, C, C++, Java, Go, or similar technologies.
  • Ability to analyze technical data, identify patterns, summarize findings, and communicate conclusions clearly.
  • Interest in large-scale systems, AI infrastructure, datacenter systems, hardware/software integration, or distributed computing.
  • Willingness to collaborate, ask questions, learn quickly, and work across engineering teams.

Responsibilities

  • Contribute to system-level designs for large-scale accelerated computing environments, including reusable reference architectures and deployment-specific solutions.
  • Evaluate, prototype, and validate emerging infrastructure, hardware, software, firmware, networking, storage, and accelerator technologies.
  • Support end-to-end system integration, bring-up, validation, and production-readiness activities across cross-functional engineering teams.
  • Define, document, and communicate engineering requirements, design tradeoffs, debug methods, findings, and recommendations.
  • Analyze workload, telemetry, performance, reliability, and operational data to identify issues and improvement opportunities.
  • Build or improve dashboards, automation, tools, and workflows that support issue detection, diagnosis, recovery, and technical decision-making.
  • Present technical work and communicate risks, blockers, status, and recommendations through design reviews, project readouts, and cross-functional forums.

Desired Qualifications

  • Academic, internship, research, or project experience with distributed systems, HPC systems, AI clusters, datacenter infrastructure, or GPU-accelerated computing.
  • Experience with Linux systems, containers, Kubernetes, Slurm, networking, storage, cloud infrastructure, or on-prem infrastructure.
  • Experience analyzing logs, metrics, telemetry, workload data, performance regressions, or reliability issues.
  • Experience building dashboards, visualizations, automation, scripts, or lightweight tools used by others.
  • Experience with hardware/software integration, firmware/software lifecycle management, validation, production operations, or system troubleshooting.
  • Examples of clear technical storytelling, such as presentations, diagrams, demos, research posters, design reviews, or written technical summaries.

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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