NVIDIA is the world leader in GPU Computing. We are passionate about markets include gaming, automotive, vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering Deep Learning software frameworks, analytics, data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and hard-working technical people across countries sounds exciting, this job is for you. NVIDIA is looking for an outstanding individual who thrives in a diverse work environment, has outstanding interpersonal skills and possesses a strong sense of engagement and continuous process improvement. This candidate must have enterprise server integration, strong Linux experience, reliability testing with various telemetries, scale out cluster, test plan development, track record in developing AI tools and NLP, DevOps, CI/CD experience to join our platform SWQA team.
What you’ll be doing:
Responsible for the development and execution of NVIDIA HGX/DGX/MGX platform test plan on servers, OS, FW and CUDA SW stack from design doc.
Installing and testing various systems OS, server firmware and SW stack.
Drive support for root cause analysis on reliability and validation test failures to identify root cause(s) and achieve mitigation.
Build, develop/debug server and OS level automation front-end and back-end framework and tests
Review partner and supplier test results and prescribe additional reliability testing on components, servers, and packaging as needed.
Work in an agile software development team with very high production quality standards.
Manage bug lifecycle and collaborate with inter-groups to drive for solutions.
What we need to see:
Bachelor’s Degree (or equivalent experience) in a STEM (Science, Technology, Engineering, Math or Physics) field
5+ years proven experience; or master’s degree.
Proven years of OS and server level automation, CI/CD process and DevOps experience using Python, SHELL, Ansible, Jenkins, C/C++, Java, JavaScript
Strong server and Linux(Ubuntu, RedHat, CentOS, SuSE, Fedora and etc…) troubleshooting and debugging experience in a bare-metal and KVM/VMWare/Hyper-V environment.
Good knowledge and hands-on experience in model testing, AI tools/frameworks (TensorFlow, Pytorch, Cursor and etc…), NLP and LLM benchmarking
Experience in using AI development tools for test plans creation, test cases development and test cases automation
Strong experience in FW, BMC/OpenBMC, Network protocol, internal/external enterprise storage devices, PCIe buses and devices, IO sub-devices, CPU and memory, ACPI, UEFI spec, Redfish - huge plus
Proven years of experience in GitHub/Gitlab/Gerrit, PXE, SLURM, Stack/Kubernetes/Docker) – huge plus
Ways to stand out from the crowd:
AI related tools, LLM and NLP.
Experience working with NVIDIA GPU hardware is a strong plus.
Good to have solid understanding of virtualization in Linux (KVM, Docker orchestrated with Kubernetes)
Background in parallel programming ideally CUDA/OpenCL is a plus
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.Skills Required
- Bachelor's degree or equivalent experience in a STEM field such as science, technology, engineering, mathematics, or physics
- At least 5 years of proven experience, or a master's degree
- Experience with OS-level and server-level automation, CI/CD, and DevOps
- Experience using Python, Shell, Ansible, Jenkins, C, C++, Java, and JavaScript
- Strong server and Linux troubleshooting and debugging experience in bare-metal and KVM, VMware, or Hyper-V environments
- Hands-on experience with model testing, AI tools or frameworks, NLP, and LLM benchmarking
- Experience using AI development tools for test-plan creation, test-case development, and test automation
- Experience with firmware, BMC/OpenBMC, network protocols, enterprise storage, PCIe, IO sub-devices, CPU and memory, ACPI, UEFI, and Redfish
- Experience with GitHub, GitLab, Gerrit, PXE, SLURM, Kubernetes, and Docker
- Experience with NVIDIA GPU hardware
- Understanding of Linux virtualization, including KVM, Docker, and Kubernetes
- Background in parallel programming using CUDA or OpenCL
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
