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Senior Software Test Development Engineer – Deep Learning

Senior Software Test Development Engineer – Deep Learning

CompanyNVIDIA
LocationSanta Clara, CA, USA
Salary$136000 – $264500
TypeFull-Time
DegreesBachelor’s
Experience LevelSenior

Requirements

  • BS or higher in CS/EE/CE or equivalent experience.
  • 4+ years of software quality assurance or test automation background with knowledge of test infrastructure and strong analysis skills.
  • Scripting language (Python, Perl, Bash) knowledge and UNIX/Linux experience.
  • Good C/C++ software development or test development experience.
  • Good user/development experiences of virtualization like VM & Docker container.
  • Understanding and working knowledge with any Deep Learning Framework and models especially in end-to-end customer scenarios.
  • Experience in validating Deep Learning software and Deep Learning models.
  • Experience in using AI development tools for test plans creation, test cases development and test cases automation.
  • Able to balance conflicting/changing priorities and maintain a positive attitude while experiencing ambitious and dynamic schedules.
  • Excellent English written and oral communication skills.

Responsibilities

  • Work closely with global multi-functional teams to understand the test requirements and take ownership of product quality.
  • Plan/design/implement/report/automate test plan/test case/test reports.
  • Run bug lifecycle and co-work with inter-groups to work towards solutions.
  • Automate test cases and assist in the architecture, crafting and implementing of test frameworks.
  • In-house repro and verify customer issues/fixes.

Preferred Qualifications

  • Familiarity with NVIDIA GPU hardware products (Tesla, Tegra, DGX, etc.); working knowledge of NVIDIA GPU Computing (CUDA) and CUDA libraries for Deep Learning.
  • Experience in building models and AI-based infrastructure to improve test automation.
  • Experience with LLM inference frameworks (TRT-LLM, vLLM, SGLang, etc.)
  • Background in validating Data Center GPU based infrastructure (multi-GPUS, multi-nodes, cluster).
  • Experience in VectorCAST, Bullseye, Gcov, or Coverity tools.