Role at a glance
- Salary
- $168K – $270.3K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 8+ years testing SW development cycle
- Education
- BS or MS in Engineering (or equivalent experience)
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Role Summary
This role joins NVIDIA's Confidential Computing QA team within the Enterprise SWQA organization. The engineer develops feature, automation, and validation infrastructure for compute software and new compute architecture platforms, supporting distributed testing across heterogeneous servers, GPUs, automation farms, and cloud environments.
What You'll Do
- Develop test plans and orchestrate testing for Compute software releases across new compute architecture platforms, Tesla GPUs, NVIDIA...
- Develop test infrastructure incorporating AI tools to enhance testing capabilities and improve operational efficiency and accuracy.
- Improve code coverage and develop roadmaps for the software development, testing, and deployment lifecycle of tools.
- Collaborate across teams to identify features and lead their definition, automation implementation, and productization.
- Build and operate automation framework infrastructure, support automation, and participate in automating manual test cases.
- Test software functionality and internal code structure, and run regression tests for CUDA and Driver features.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
BS or MS in Engineering or equivalent experience; 8+ years testing the software development cycle; solid understanding of embedded systems, Linux, Python, C, and C++; experience with AI tools for automation and test plan development; strong technical skills in orchestration and automation systems, data centers, and cloud architecture; understanding of QA methodology, clusters and cluster management; experience developing test strategies, test plans, test execution, and HW/SW test setups.
Required
- Embedded systems
- Linux
- Python
- C
- C++
- AI tools for automation and test plan development
- Orchestration and automation systems
- Data centers and cloud architecture
Preferred
- Hypervisors
- Cloud infrastructure
- Platform security
- Highly regulated deployment environments
- Embedded system features
- Software and hardware stacks
- AI-powered tools for test case, plan, and script generation, defect detection, CBTP, and bug fixing
- Ansible
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.