Role at a glance
- Salary
- $184K – $356.5K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years of system software validation experience.
- Education
- BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience).
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The CSP Engagements team is seeking a Senior Systems Software Test Lead Engineer to validate ML software stacks for datacenter products including GB200 and Vera Rubin. The role works across hardware and software from cluster to rack scale, partnering with cloud service providers and NVIDIA teams to support stable, performant training and inference platforms through deployment.
What You'll Do
- Define test strategies and validation plans for CSP integration milestones, identify methodology gaps, and provide recommendations.
- Reproduce, characterize, and triage customer bugs in customer environments and local labs.
- Review test plans and results, publish release test reports, and validate fixes, mitigations, and release updates.
- Partner with NVIDIA development teams on root-cause analysis and release-readiness decisions using pass/fail evidence.
- Collaborate with CSP teams on provisioning, access, break-fix workflows, and environment readiness, producing release-readiness summaries.
- Manage testing output datasets, develop tooling for debug-data retrieval and visualization, and run performance benchmarks for training...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Experience in validation, QA, system test, diagnostics, platform bring-up, or release qualification for complex hardware-software systems; understanding of server platforms, firmware, drivers, OS integration, networking, and large-scale cluster environments; hands-on debugging across hardware, firmware, software, networking, and infrastructure layers; Linux, shell scripting, Python, test automation, test infrastructure design, and CI/regression workflows; experience creating test plans, regression suites, validation reports, and defect documentation; strong cross-functional communication skills.
Required
- Experience in validation, QA, system test, diagnostics, platform bring-up, or release qualification for complex hardware-software systems
- Understanding of server platforms, firmware, drivers, OS 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 CI/regression workflows
- Experience creating test plans, regression suites, validation reports, and defect documentation
- Proficient in Python with strong background in test automation and test infrastructure design
- BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience)
Preferred
- Hands-on experience in cloud and cluster-level deployment and ML Ops
- Experience in running deep learning workloads and related automation
Original job description
Content provided by the employer
Original job description
Content provided by the employer
NVIDIA is seeking a Senior Systems Software test (lead) Engineer to join our Cloud Service Provider (CSP) Engagements team, focusing on ML software stack validation for Datacenter products such as GB200 and Vera Rubin. This role combines deep technical expertise from cluster to rack scale full-stack validation with customer-facing responsibilities, enabling cloud service providers with next-generation high-performance training and inference platforms. You will work at the intersection of hardware and software, validating stable and performant technical solutions from concept through deployment.
What you will be doing:
Define test strategy and test validation plans for CSP integration milestones, partner with hyper scalars to understand their test methodology, identify gaps and provide NVIDIA recommendations.
Reproduce, characterize, and triage customer bugs in the customer environment. Review internal test plans, test results, and publish summary test report for each release for the rack scale product during NPI phases.
Validate fixes, mitigations, and release updates against deployed CSP software modules and known-good partner configurations.
Partner with NVIDIA development teams to drive root-cause analysis and confirm release readiness with clear pass/fail evidence
Collaborate with CSP teams on provisioning, access, break-fix workflows, and environment readiness. Produce concise release-readiness summaries for internal stakeholders and partner-facing engineering reviews.
Manage large datasets of testing output and develop tooling for efficient retrieval of debug data, visualization, and reporting experience with tools.
Work with customers to localize problems using targeted reproduction steps by enabling stress and edge-case testing to assist development teams.
Running perf benchmarks for both training and inference. Collaborate with AE, FAE, and Solution Architect teams on validation for customer issues and technical documentation. Replicate the reported problems in the local lab
What we need to see:
Experience in validation, QA, system test, diagnostics, platform bring-up, or release qualification for complex hardware-software systems.
Strong understanding of server platforms, firmware, drivers, OS 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 CI/regression workflows. Experience creating test plans, regression suites, validation reports, and defect documentation.
Strong cross-functional communication skills with QA, development, field, support, and customer engineering teams.
Proficient in Python with strong background in test automation and test infrastructure design. Able to communicate effectively and collaborate with partner and customer teams.
BS or MS in Computer Engineering, Computer Science, or related field (or equivalent experience).
8+ years of system software validation experience.
Ways to stand out from the crowd:
Hands-on experience in cloud and cluster-level deployment and ML Ops.
Experience in running deep learning workloads and related automation
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, hardworking and self-motivated, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.