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Nvidia Senior Software Test Development Engineer - NVLink Fusion 
China, Shanghai 
590140326

28.07.2025
China, Shanghai
time type
Full time
posted on
Posted 6 Days Ago
job requisition id

What you’ll be doing:

  • Work closely with global cross-functional teams to understand the test requirements and take ownership of product quality.

  • Plan/design/execute/report/automatetest plan/test case/test reports.

  • Manage bug lifecycle and co-work with inter-groups to drive for solutions.

  • Automate test cases and assist in the architecture, crafting and implementing of test frameworks.

  • In-house repro and verify customer issues/fixes.

What we need to see:

  • BS or higher degree in CS/EE/CE or equivalent.

  • 5+ years of software quality assurance or test automation background with knowledge of test infrastructure and strong analysis skills.

  • Scripting language (Python, Bash) knowledge and UNIX/Linux experience.

  • Good Python software development or test development experience.

  • Good user/development experience of virtualization like VM & Docker container & k8s

  • Excellent English written and oral communication skills.

  • Multiple GPUs P2P workload developing/testing

  • Able to juggle conflicting/changing priorities and maintain a positive attitude while experiencing challenging and dynamic schedules.

  • Proven success in leveraging AI (development) tools to significantly improve efficiency, streamline workflows, enhance process automation, create test cases and increase code coverage.

  • Experiencewith LLM inference frameworks (TRT-LLM, vLLM, SGLang, etc.) and familiar with running various AI workloads

  • Experience with AI tools for coding (like Cursor, Gemini, NotebookLM)

Ways to stand out from the crowd:

  • Familiarity with NVIDIA GPU hardware products (Tesla, Tegra, DGX, etc.)

  • Familiarity with multiple GPUs tools usage (NCCL / NIXL)

  • Understanding and working knowledge with any Deep Learning Framework especially in end-to-end customer scenarios.

  • Working knowledge of NVIDIA GPU Computing (CUDA) and CUDA libraries for Deep Learning like cuDNN

  • Experience in VectorCAST, Bullseye, Gcov, or Coverity tools.