We are looking for Senior Software Development Engineer in Test to join our Confidential Computing team for NVIDIA's Enterprise SWQA team. Are you passionate about new feature development, automation development, test and validation infrastructure? Do you excel using AI tools to aid in solving complex issues? We'd love to have your skills on the team!
As an engineer on this Confidential Computing QA team, you will do many feature development that include test plan development, automate testbench independent test specification and execution workflows for worldwide chip validation teams running tests on silicon along with automation framework/infrastructure development. You will develop a system operating at large scale, running hundreds of tests per day in distributed heterogeneous servers with NVIDIA's GPUs connect to verify multiple designs/POR in many configurations those are sitting in automation farm or in cloud. You will continuously innovate and develop scalable, reliable, high performance systems and tools to enable the next generation of chips.
What you’ll be doing:
Develop test plan and orchestrate testing for Compute software releases on all new compute architecture platforms including Tesla GPUs, NVIDIA turnkey systems and OEM systems.
Develop a robust test infrastructure incorporating advanced AI tools to significantly enhance our testing capabilities and streamlining operations for more efficient and accurate results.
Improve code coverage, elevating the overall quality of our codebase and reliability of our testing processes and develop roadmaps prioritizing software development schedule for full life-cycle 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 timely manner
Build and operate key pieces of a complete infrastructure for automation framework development, as well as, lead and develop automation support and participate in automation of manual test cases, working closely with automation infrastructure
Focus on an efficient customer experience by improving both usability and ease to attain optimal performance
Test both software functionality and internal code/structure and 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 8+ years testing SW development cycle.
Solid understanding of embedded systems, Linux, Python, C and C++.
Experience with Hypervisors is a big plus along with focus on cloud infrastructure, platform security, or highly regulated deployment environments.
Proven experience with AI tools for automation and test plan development directly applied to daily tasks. This expertise is crucial for enhancing performance, developing robust frameworks, and increasing test coverage.
Strong technical skills, with deep understanding of orchestration & automation systems, data centers and cloud architecture combined.
Solid understanding in QA methodology and pay attention to details.
Knowledge in Cluster and cluster management.
Experience in developing test strategies, high quality test plans and test execution
Proficient in building test setups and fine tuning in HW and SW
Ways to stand out from the crowd:
Expertise in developing embedded system features, combined with solid knowledge of both software and hardware stacks.
Apply AI-powered tools to improve efficiency and quality, including test case/plan/script generation, defect detection, CBTP, bug fixing and day to day assistance
Experience with Configuration and deployment management (Ansible), Containers (Docker) and Virtualization infrastructure software (Xen, KVM,Hyper-V)
Good understanding of C/C++ toolchain in Linux including cross-compilation (C, C++, automake/autoconf, cmake, meson).
Background with parallel programming, ideally CUDA C/C++ and OpenACC
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- BS or MS in Engineering (or equivalent experience) with 8+ years testing software development cycle
- Solid understanding of embedded systems, Linux, Python, C and C++
- Proven experience with AI tools for automation and test plan development
- Deep understanding of orchestration and automation systems, data centers and cloud architecture
- Solid understanding of QA methodology and strong attention to detail
- Knowledge in 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
- Experience with Hypervisors and virtualization infrastructure (Xen, KVM, Hyper-V)
- Experience with configuration and deployment management (Ansible) and containers (Docker)
- Familiarity with C/C++ toolchain in Linux including cross-compilation, automake/autoconf, CMake, Meson
- Background in parallel programming, ideally CUDA C/C++ and OpenACC
- Expertise in embedded system features and full HW/SW stack knowledge
- Experience applying AI-powered tools for test generation, defect detection, and automation
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
