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NVIDIA

Designs the chips and software that power AI

Data Center Power Test Architect

Test Automation EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A B.S., M.S., or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent experience.
  • At least 10 years of experience in data center power enablement related to software or firmware testing, focused on telemetry and power efficiency across systems.
  • Strong knowledge of system architecture, power shelves, baseboard management, hardware and software power features, industry power standards, system interfaces, and embedded controllers.
  • Experience designing test frameworks and infrastructure using Python, C/C++, or similar languages.
  • Expertise with platform standards for security, telemetry, and manageability, including NIST, DMTF, and OCP; hands-on experience with server platforms, networking, storage, cluster configuration, and debugging.
  • Background with platform telemetry and data center node lifecycle management or support, including CPU/GPU workloads; proficiency in scripting languages such as Python.
  • Expertise administering, operating, and configuring Kubernetes and Envoy; validated experience with CI/CD tools such as GitLab and Jenkins and the GitOps model.
  • Experience with lab automation, simulation, hardware-in-the-loop testing, and CI/CD pipelines such as Jenkins and GitLab.
  • Strong debugging, problem-solving, and analytical skills.
  • Experience using AI-powered tools and copilots to accelerate test development, automate repetitive validation workflows, and streamline debugging and root cause analysis.

Responsibilities

  • Define and drive end-to-end test architecture and validation strategy for power features across NVIDIA platforms, from pre-silicon simulation and emulation through post-silicon bring-up and production readiness.
  • Develop test plans aligned with product deliverables and customer use cases; work across teams to ensure comprehensive test coverage and influence early design decisions to improve testability and automation readiness.
  • Design and implement modular, reusable test frameworks and automation harnesses for functional, integration, stress, regression, power, security, and performance testing, scaling across hundreds of systems in parallel.
  • Define data center power quality KPIs, including code coverage, system uptime, bug escape rate, and validation completeness; establish dashboards and reporting to track progress and support data-driven decisions.
  • Lead complex investigations across firmware, software, and hardware; develop and document debugging methodologies and tools to improve diagnosis efficiency across the team.
  • Partner with DevOps and infrastructure teams to enhance test automation pipelines, integrate continuous testing into nightly and pre-merge workflows, and support fast, reliable release qualification.
  • Validate real-world use cases, customer configurations, and production scenarios; contribute to release gates and sign-off criteria for firmware deployment in mission-critical systems.
  • Mentor and coach software QA engineers and junior test developers, foster quality and continuous learning, and champion tools, methodologies, and standards that raise quality.
  • Stay current with trends in embedded validation, test automation frameworks, and industry standards; champion adoption of emerging technologies and practices.

Desired Qualifications

  • Experience with NVIDIA platforms such as DGX, HGX, or Grace Hopper systems.
  • Exposure to security validation, compliance such as FIPS or BMC security, or thermal and power validation.
  • Prior experience as a test architect or technical lead for large-scale data center enablement or firmware validation programs.
  • Contributions to open-source testing tools or frameworks, with strong knowledge of cloud-scale validation, infrastructure automation, or virtualization.
  • Prior experience using AI tools to create agents, design test plans, identify test gaps, automate workflows, and conduct failure analysis.
  • Experience working in a globally distributed team.

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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