Used Tools & Technologies
GPURequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Software Development @ 4
Ansible @ 4
Docker @ 4
Linux @ 6
Python @ 6
Parallel Programming @ 4
QA @ 4
Agile @ 4
CUDA @ 4
Cloud Computing @ 6
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
We are looking for a Senior Software Development Engineer in Test to join the Compute CUDA Quality Assurance team for NVIDIA's Enterprise SWQA release schedules. The role focuses on automation development, test and validation infrastructure, and applying AI tools to solve complex testing and automation problems. You will automate testbench-independent test specification and execution workflows for worldwide chip validation teams running tests on silicon and develop automation framework/infrastructure to operate at large scale across distributed heterogeneous servers with NVIDIA GPUs.
Responsibilities
- Develop test plans and orchestrate testing for Compute software releases across new compute architecture platforms (Tesla GPUs, NVIDIA turnkey systems, OEM systems).
- Develop and operate robust test infrastructure incorporating advanced AI tools to enhance testing capabilities and streamline operations.
- Improve code coverage and reliability; develop roadmaps for full life-cycle tool development, testing, and deployment.
- Collaborate across teams to identify new features and lead developers in defining, implementing automation, and productizing features.
- Build and operate key pieces of a complete automation framework and provide automation support, including automating manual test cases.
- Improve customer experience by enhancing usability and performance attainment.
- Test software functionality and internal code structure; run regression tests for existing CUDA/Driver features.
- Work in a dynamic agile software development team with very high production quality standards.
Requirements
- BS or MS in Engineering (or equivalent experience) with 5+ years in the software testing/development cycle.
- Solid understanding of embedded systems.
- Proficient with Linux, Python, C, and C++.
- Proven experience using AI tools for automation and test plan development applied to daily tasks.
- Strong technical skills and deep understanding of orchestration & automation systems, data centers, and cloud architecture.
- Knowledge of QA methodology, attention to detail, and experience developing test strategies, high-quality test plans, and executing tests.
- Experience with cluster and cluster management.
- Proficiency in building test setups and fine-tuning hardware and software components that enable cloud computing services.
Ways to stand out
- Hands-on experience with cloud infrastructure (designing, deploying, maintaining scalable systems on major cloud platforms).
- Applying AI-powered tools to improve efficiency and quality (test case/plan/script generation, defect detection, bug fixing, etc.).
- Experience with configuration and deployment management (Ansible), containers (Docker), and virtualization software (Xen, KVM).
- Good understanding of C/C++ toolchain in Linux including cross-compilation (automake/autoconf, cmake, meson).
- Background with parallel programming, ideally CUDA C/C++ and OpenACC.
Compensation
- Base salary range: 140,000 USD - 224,250 USD for Level 3, and 168,000 USD - 270,250 USD for Level 4.
- You will also be eligible for equity and benefits.
Additional information
- Applications accepted at least until April 17, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.