NVIDIA

Performance Engineering Intern - 2027

In short

NVIDIA is hiring a Performance Engineering Intern to join its Performance Lab team, benchmarking and optimizing GPU performance across gaming, workstation, AI/LLM and system workloads. The role involves designing benchmark methodologies, writing competitive analysis reports, and building automation scripts and tools for performance testing on Windows and Linux. It requires a student pursuing a CS-related degree with Python scripting skills, PC systems knowledge, and passion for PC games or local AI; familiarity with NVIDIA GPUs, graphics APIs, AI agents, or containerization is a plus.

About the Role
We are now looking for a Consumer & Enterprise Performance Engineer Intern! This position offers the chance to create a significant impact in a dynamic, technology focused company. As a member of the Performance Lab team, you will reach firsthand GPUs and optimize performance from designing stage till whole product lifetime, architectures to extend the state of the art in Gaming, Professional Visualization, Local AI efficiency and performance.
What you'll be doing:
•Design, config and execute representative benchmark methodologies and real-world use cases that showcase product capabilities across AI/LLM, gaming, workstation, content-creation, and system workloads across servers, PCs, workstations, SoC and laptops.
•Compose competitive analysis reports for internal and external customers to position NVIDIA products appropriately using their evaluation.
•Develop and maintain automation scripts for games/studio/WinAI performance and system monitoring data collection on Windows and Linux to speed up providing business and engineering insights.
•Develop, implement and maintain tools to improve testing efficiency.
What we need to see:
•Pursuing BS or MS degree in Computer Science or similar computer discipline.
•Good knowledge of Python or other scripting languages.
•Good knowledge of PC systems and components.
•Experienced and passionate about PC games or local AI.
•Linux and Windows knowledge.
•Capability to work with a lot of data.
•Good organizational, time management and task prioritization skills.
Ways to stand out from the crowd:
•Familiarity with NVIDIA GPUs and NVIDIA Technologies.
•Knowledge of OpenGL, Direct X and D3D.
•Experience developing AI agents or agentic workflows.
•Knowledge of containerized and virtualized workflows, including Docker, Kubernetes, and virtual machines.

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