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NVIDIA

Applied Systems Engineering Rotation Engineer - New College Graduate 2026

NVIDIA is hiring an Applied Systems Engineering Rotation Engineer - New College Graduate 2026 in Santa Clara, United States. It pays $108k-$178k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Little AI ●○○○ is how Level rates this role: aI is not part of the work.
  • Level classes it as a junior role.
  • NVIDIA has 2,700+ other open roles on Level.

AI in this role

NVIDIA is looking for enthusiastic New College Graduates to join the Applied Systems Engineering team in a 12-month rotation program. ASE engages with the entire lifecycle of next-generation AI supercomputing pre-clusters at scale. The team creates reference architectures, confirms feasibility through initial end-to-end integration and bring-up, and supports large-scale production environments. These environments allow internal teams to run workloads, gather detailed telemetry, and detect and resolve issues before they impact customers.

As an Applied Systems Engineering Rotation Engineer, you will move through different teams such as Architecture, Bring-up, and Production. Exposure to software, performance, or technical program management teams is possible when program needs align. Throughout four 3-month rotations, you will collaborate with senior engineers and mentors on projects that help NVIDIA design, integrate, validate, operate, and improve large-scale GPU compute clusters. This program is intended for New College Graduates who are curious, systems-minded, and eager to learn how architecture decisions become production-ready clusters. At the end of the year, final placement will be based on a combination of business need, host manager feedback, demonstrated strengths, and candidate preference.

What you’ll be doing:

  • 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.

What we need to see:

  • 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.

  • Strong collaboration and communication skills, with a willingness to ask questions, learn quickly, and work across engineering teams.

Ways to stand out from the crowd:

  • 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.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
108,000 USD – 178,250 USD for Level 1; and 124,000 USD – 195,500 USD for Level 2.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 6, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Applied Systems Engineering Rotation Engineer - New College Graduate 2026 at NVIDIA rates 11 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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