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NVIDIA

Designs the chips and software that power AI

Lead Systems Software Test Engineer - CSP Engagements

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

About the Job

Requirements

  • Experience in validation, quality assurance, system testing, diagnostics, platform bring-up, or release qualification for complex hardware-software systems.
  • Strong understanding of server platforms, firmware, drivers, operating system integration, networking, and large-scale cluster environments.
  • Hands-on experience debugging issues across hardware, firmware, software, networking, and infrastructure layers.
  • Ability to analyze logs, telemetry, diagnostic outputs, automation failures, and system health signals.
  • Familiarity with Linux environments, shell scripting, Python or similar automation, and continuous integration/regression workflows.
  • Experience creating test plans, regression suites, validation reports, and defect documentation.
  • Strong cross-functional communication with quality assurance, development, field, support, and customer engineering teams.
  • Proficiency in Python, with a strong background in test automation and test infrastructure design.
  • Ability to communicate and collaborate effectively with partner and customer teams.
  • Bachelor of Science or Master of Science in Computer Engineering, Computer Science, or a related field, or equivalent experience.
  • At least 8 years of system software validation experience.

Responsibilities

  • Define test strategy and test validation plans for cloud service provider integration milestones; partner with hyperscalers to understand their test methodologies, identify gaps, and provide recommendations.
  • Reproduce, characterize, and triage customer bugs in customer environments.
  • Review internal test plans and test results, and publish a summary test report for each rack-scale product release during new product introduction phases.
  • Validate fixes, mitigations, and release updates against deployed cloud service provider software modules and known-good partner configurations.
  • Partner with development teams to drive root-cause analysis and confirm release readiness with clear pass/fail evidence.
  • Collaborate with cloud service provider teams on provisioning, access, break-fix workflows, and environment readiness.
  • Produce release-readiness summaries for internal stakeholders and partner-facing engineering reviews.
  • Manage large testing-output datasets and develop tools for efficient debug-data retrieval, visualization, and reporting.
  • Work with customers to localize problems using targeted reproduction steps and stress and edge-case testing to assist development teams.
  • Run performance benchmarks for training and inference.
  • Collaborate with application engineering, field application engineering, and solution architect teams on customer-issue validation and technical documentation.
  • Replicate reported problems in the local lab.

Desired Qualifications

  • Hands-on experience in cloud and cluster-level deployment and machine learning operations.
  • Experience running deep learning workloads and related automation.

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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