Applied Systems Engineering Rotation Engineer - New College Graduate 2026

NVIDIA•Us, CA

About The Position

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.

Requirements

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.

Nice To Haves

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.

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.