Senior Software QA Test Development Engineer - Diagnostics
NVIDIAJob Title
Senior Software QA Test Development Engineer - Diagnostics
Role Summary
Join NVIDIA's platform software QA team to develop and execute reliability and validation test plans for HGX/DGX/MGX server platforms. The role focuses on server, OS, firmware and CUDA software stack testing, root-cause analysis, and automation for large-scale cluster environments.
Experience Level
Senior role. Expect 5+ years of relevant experience (or equivalent); a Master's degree is noted as an alternative to additional experience in the posting.
Responsibilities
Primary responsibilities include test development, execution, and analysis across server platforms and software stacks.
- Develop and execute platform test plans for servers, OS, firmware, and CUDA software stacks.
- Install and validate system OS, server firmware, and software stacks on bare-metal and virtualized systems.
- Drive root-cause analysis for reliability and validation test failures and produce mitigations.
- Design, build, and maintain front-end and back-end test automation frameworks and tests.
- Review partner and supplier test results and recommend additional reliability testing as needed.
- Work inside an agile software development process and manage bug lifecycle with cross-team collaboration.
Requirements
Must-have technical skills and experience; plus items indicate added advantage.
- Must-have: Proven OS and server-level automation experience and familiarity with CI/CD and DevOps workflows.
- Must-have: Strong Linux troubleshooting and debugging on bare-metal and virtualized environments (KVM, VMware, Hyper-V).
- Must-have: Practical experience with automation and scripting using Python and shell; exposure to Ansible and Jenkins.
- Must-have: Experience working with storage, network protocols, PCIe, CPU/memory subsystems, and system diagnostics.
- Must-have: Experience developing and running validation/reliability tests at scale (cluster/SLURM/Kubernetes/Docker usage noted).
- Nice-to-have: Experience with AI frameworks and model testing (TensorFlow, PyTorch), LLM/NLP benchmarking, and AI-assisted test development.
- Nice-to-have: Firmware/BMC (OpenBMC), Redfish, PXE, GitHub/GitLab/Gerrit, SLURM, Kubernetes, Docker, and virtualization orchestration experience.
- Nice-to-have: Background in CUDA/OpenCL or prior experience with NVIDIA GPU hardware.
Education Requirements
Bachelor's degree in a STEM field (Science, Technology, Engineering, Math, or Physics) or equivalent practical experience; a Master’s degree is listed as an acceptable alternative to additional years of experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
