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NVIDIA

Designs the chips and software that power AI

Performance Engineer

Performance TestingConfirmed live in the last 24 hours
Full-timeShanghai, ChinaNo salary listedIn-person

About the Job

Requirements

  • A Bachelor of Science or Master of Science degree.
  • At least 2 years of 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 and large language model workloads, PC gaming, workstation applications, and content-creation workflows.
  • A solid understanding of PC and server architecture.
  • Experience working with large datasets.
  • Strong analytical and troubleshooting skills.
  • Excellent communication, organizational, time-management, and task-prioritization skills.

Responsibilities

  • Design, configure, and execute representative benchmark methodologies and real-world use cases that showcase product capabilities across AI and large language model, gaming, workstation, content-creation, and system workloads on servers, PCs, workstations, systems-on-chip, and laptops.
  • Analyze performance metrics and system telemetry to identify bottlenecks, regressions, and optimization opportunities.
  • Produce clear, data-driven competitive analyses and technical reports to help internal and external stakeholders position NVIDIA products effectively.
  • Develop and debug automation scripts for benchmark performance and system-monitoring data collection on Windows, Linux, and macOS.
  • Build and maintain scalable automation frameworks, AI agents, dashboards, and data pipelines to improve testing efficiency, coverage, and analytical robustness.

Desired Qualifications

  • Familiarity with NVIDIA GPUs and NVIDIA technologies.
  • Working knowledge of AI inference or training and fine-tuning concepts.
  • Experience building, benchmarking, or operating AI platforms and large language model inference stacks.
  • Experience developing AI agents or agentic workflows.
  • Knowledge of containerized and virtualized workflows, including Docker, Kubernetes, and virtual machines.

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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