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Performance Engineer

NVIDIA

Shanghai, Shanghai, ChinaFull-timePosted 3w agoStill listed today

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At a glance

Compensation
No compensation found
Location
Shanghai, Shanghai, China
Schedule
Full-time
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Bachelor's degree

Job overview

NVIDIA seeks a Performance Engineer for its Shanghai Perflab to design, execute, and analyze benchmark methodologies across AI, gaming, and workstation workloads, producing data‑driven reports and building automation frameworks to enhance testing efficiency and product performance.

Skills & qualifications

RequiredNice to have

Skills

PythonWindowsLinuxMacOSAI LLM WorkloadsPC GamingWorkstation ApplicationsContent Creation WorkflowsPC and Server ArchitectureLarge DatasetsCommunicationOrganizational SkillsTime ManagementTask PrioritizationNVIDIA GPUsNVIDIA TechnologiesAI InferenceAI TrainingFinetuning ConceptsAI PlatformsLLM Inference StacksAI AgentsContainerized WorkflowsVirtualized WorkflowsDockerKubernetesVirtual Machines

Qualifications

BS or MS Degree2+ Years Equivalent Practical Experience

Full job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

Are you ambitious and ready to make a significant impact in a dynamic, technology-focused company? At NVIDIA, we're looking for a Performance Engnieer to join our outstanding Perflab in Shanghai. This role offers an outstanding opportunity to work with innovative GPUs and optimize performance from the design stage through the entire product lifecycle. Join us and be part of a team that extends the state-of-the-art in gaming, professional visualization, Omniverse, efficiency!

What you will 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.

  • Analyze performance metrics and system telemetry to identify bottlenecks, regressions, and optimization opportunities.

  • Produce clear, data-driven competitive analyses and technical reports that help internal and external stakeholders position NVIDIA products effectively.

  • Develop and debug automation scripts for various benchmark performance and system monitoring data collection on Windows, Linux and MacOS.

  • Build and maintain scalable automation frameworks, AI agents, dashboards, and data pipelines that improve testing efficiency, coverage, and analytical robustness.

What we need to see:

  • BS or MS degree

  • 2+ years equivalent practical experience, in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field.

  • Strong Python skills or proficiency in another scripting or programming language.

  • Hands-on interest in AI/LLM workloads, PC gaming, workstation applications, and content-creation workflows.

  • Solid understanding of PC and server architecture.

  • Experience working with large datasets, and strong analytical and troubleshooting skills.

  • Excellent communication, organizational, time management, and task prioritization skills.

Ways to stand out from the crowd:

  • Familiarity with NVIDIA GPUs and NVIDIA Technologies.

  • Working knowledge of AI inference or training, finetuning concepts.

  • Experience building, benchmarking, or operating AI platforms and LLM inference stacks.

  • Experience developing AI agents or agentic workflows.

  • Knowledge of containerized and virtualized workflows, including Docker, Kubernetes, and virtual machines.

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