NVIDIA
Senior Software Development Engineer in Test
We are looking for a Senior Software Development Engineer in Test to join our New GPU Integration (NPI) team for NVIDIA's Enterprise Compute SWQA team. You will contribute to feature development, automation development, test and validation, bug fixing, and test content creation using C/C++. You will work on AI-assisted tooling to solve complex issues and help build scalable, high-performance validation systems.
Base pay range $168,000.00/yr - $264,500.00/yr
Base salary information is provided in the job post. You will also be eligible for equity and benefits.
What You’ll Be Doing
Develop test plans and orchestrate testing for Compute software releases on new compute architecture platforms including Tesla GPUs, NVIDIA turnkey systems and OEM systems.
Develop a robust test infrastructure incorporating AI tools to enhance testing capabilities and streamline operations for efficient and accurate results.
Improve code coverage and the reliability of testing processes; develop roadmaps prioritizing software development and the full lifecycle of tool development, test, and deployment.
Collaborate across teams to identify new features and lead developers in definition, automation implementation, and productization of those features in a timely manner.
Build and operate key components of the automation framework, lead automation support, and participate in automating manual test cases in coordination with automation infrastructure.
Focus on an efficient customer experience by improving usability and attainment of optimal performance.
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.
What We Need To See
BS or MS in Engineering (or equivalent experience) with 7+ years of testing software development life cycle.
Solid understanding of embedded systems, Linux, Python, C and C++.
Very good knowledge of Linux and Windows packages.
Experience with Hypervisors is a big plus.
Proven experience with AI tools for automation and test plan development directly applied to daily tasks.
Strong technical skills with understanding of orchestration & automation systems, data centers and cloud architecture.
Solid understanding of QA methodology and attention to detail.
Knowledge of cluster and cluster management.
Experience in developing test strategies, high-quality test plans, and test execution.
Proficient in building test setups and fine-tuning hardware and software.
Ways To Stand Out From The Crowd
Expertise in developing embedded system features with knowledge of software and hardware stacks.
Apply AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, and day-to-day assistance.
Experience with configuration and deployment management (Ansible), containers (Docker) and virtualization infrastructure software (Xen, KVM).
Good understanding of the C/C++ toolchain in Linux including cross-compilation (C, C++, automake/autoconf, cmake, meson).
Background with parallel programming, ideally CUDA C/C++ and OpenACC.
NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Applications for this job will be accepted at least until October 28, 2025.
JR2006792
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Base pay range $168,000.00/yr - $264,500.00/yr
Base salary information is provided in the job post. You will also be eligible for equity and benefits.
What You’ll Be Doing
Develop test plans and orchestrate testing for Compute software releases on new compute architecture platforms including Tesla GPUs, NVIDIA turnkey systems and OEM systems.
Develop a robust test infrastructure incorporating AI tools to enhance testing capabilities and streamline operations for efficient and accurate results.
Improve code coverage and the reliability of testing processes; develop roadmaps prioritizing software development and the full lifecycle of tool development, test, and deployment.
Collaborate across teams to identify new features and lead developers in definition, automation implementation, and productization of those features in a timely manner.
Build and operate key components of the automation framework, lead automation support, and participate in automating manual test cases in coordination with automation infrastructure.
Focus on an efficient customer experience by improving usability and attainment of optimal performance.
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.
What We Need To See
BS or MS in Engineering (or equivalent experience) with 7+ years of testing software development life cycle.
Solid understanding of embedded systems, Linux, Python, C and C++.
Very good knowledge of Linux and Windows packages.
Experience with Hypervisors is a big plus.
Proven experience with AI tools for automation and test plan development directly applied to daily tasks.
Strong technical skills with understanding of orchestration & automation systems, data centers and cloud architecture.
Solid understanding of QA methodology and attention to detail.
Knowledge of cluster and cluster management.
Experience in developing test strategies, high-quality test plans, and test execution.
Proficient in building test setups and fine-tuning hardware and software.
Ways To Stand Out From The Crowd
Expertise in developing embedded system features with knowledge of software and hardware stacks.
Apply AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, and day-to-day assistance.
Experience with configuration and deployment management (Ansible), containers (Docker) and virtualization infrastructure software (Xen, KVM).
Good understanding of the C/C++ toolchain in Linux including cross-compilation (C, C++, automake/autoconf, cmake, meson).
Background with parallel programming, ideally CUDA C/C++ and OpenACC.
NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Applications for this job will be accepted at least until October 28, 2025.
JR2006792
#J-18808-Ljbffr