Nvidia Senior Software QA Test Development Engineer 

United States, California 

221446432

What you’ll be doing:

• Responsible for the development and execution of NVIDIA HGX/DGX/MGX platform test plan on OS, FW and CUDA SW stack from design doc.

• Installing and testing various systems OS, system 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 system 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, systems, 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 with 2+ years of meaningful work experience

• Proven years of OS and server level automation experience using Python, SHELL, Ansible, Jenkins, C/C++, Java, JavaScript

• Strong OS(Ubuntu, RedHat, CentOS, SuSE, Fedora, Windows and etc…) trouble-shooting and debugging experience in a bare-metal and KVM/VMWare/Hyper-V environment.

• Ability to write test plans focusing on functional, performance, stress and negative testing.

• Experience in developing CI/CD automation processes and DevOps contribution with a real passion for automation.

• Good teamwork with ability to work independently.

• 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 inGitHub/Gitlab/Gerrit,PXE, SLURM,Stack/Kubernetes/Docker)– huge plus

Ways to stand out from the crowd:

• Experience working with NVIDIA GPU hardware is a strong plus.

• Good to have solid understanding of virtualization in Linux (KVM, Docker orchestrated with Kubernetes)

• Expertise in packaging software in Linux (rpm, debs)

• Background in parallel programming ideally CUDA/OpenCL is a plus