Nvidia is looking for a Test Development Engineer to validate our GPU Communications Libraries and build robust automation frameworks. You will join a diverse, supportive environment where everyone is inspired to do their best work.
What You'll Do
- Run test cases to validate NVIDIA GPU Communications Libraries (NCCL, NVSHMEM, UCX, GDRCopy, GPUDirect RDMA).
- Automate test cases and maintain the automation scripts.
- Collaborate with Developer, PM, marketing, and engineering teams on crafting test plans and implementing validation.
- Assist in the architecture, crafting and implementing of SWQA test frameworks.
- Be responsible for code coverage improvement and code complexity optimization.
What We're Looking For
- BS or higher degree in CS, EE, CE or equivalent experience.
- 5+ years of relevant experience.
- Seasoned software QA or software testing background; test infrastructure and strong analysis skills.
- Proficient in scripting language (Python, Perl, bash).
- Solid experience with AI development tools for test development and automation.
- Knowledge of basic networking concepts.
- UNIX/Linux experience is required.
- Experience in C/C++ is required.
- Ability to work independently and leadership skills as well as experience in using a quality mindset to drive improvements.
- Proficient oral and written English.
Nice to Have
- Experience with CUDA programming and NVIDIA GPUs.
- Knowledge of high-performance networks like InfiniBand, RoCE.
- Experience with CSPs (AWS, Google Cloud, Oracle Cloud Infrastructure, Microsoft Azure), and HPC cluster, slurm, ansible.
- Prior experience with virtualization technologies (KVM, HyperV, VMWARE, OpenStack, Docker, Kubernetes).
- Experience with Deep Learning Frameworks such as PyTorch, TensorFlow.
Technical Stack
- Scripting & Languages: Python, Perl, bash, C/C++
- Platforms & Tools: UNIX/Linux, AI development tools, CUDA, NVIDIA GPUs
- Networking: InfiniBand, RoCE
- Cloud & Infrastructure: AWS, Google Cloud, Oracle Cloud Infrastructure, Microsoft Azure, slurm, ansible
- Virtualization: KVM, HyperV, VMWARE, OpenStack, Docker, Kubernetes
- Frameworks: PyTorch, TensorFlow
Work Mode
This role follows a hybrid work model.
Nvidia is an equal opportunity employer.
