Role at a glance
- Salary
- $140K – $270.3K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years testing SW development cycle
- Education
- BS or MS in Engineering (or equivalent experience)
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Role Summary
The Senior Software Development Engineer in Test will join NVIDIA’s Compute CUDA Quality Assurance team to develop automation, test execution workflows, and infrastructure for software releases and chip validation. The role supports large-scale testing across distributed heterogeneous servers, GPUs, automation farms, and cloud environments for multiple compute architectures and configurations.
What You'll Do
- Develop test plans and orchestrate testing for Compute software releases across new compute architecture platforms.
- Develop scalable automation frameworks and infrastructure for distributed test specification and execution workflows.
- Improve code coverage and create roadmaps for the full lifecycle of tool development, testing, and deployment.
- Collaborate across teams to identify features and lead their automation implementation and productization.
- Build and operate infrastructure for automation framework development and support automation of 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; 5+ years testing the software development cycle; understanding of embedded systems, Linux, Python, C, C++, orchestration and automation systems, data centers, cloud architecture, QA methodology, cluster management, test strategies, test plans, and test execution; experience with AI tools for automation and test plan development; proficiency building and fine-tuning hardware and software test setups.
Required
- Embedded systems
- Linux
- Python
- C
- C++
- Orchestration and automation systems
- Data centers and cloud architecture
- QA methodology
Preferred
- Linux software packaging with rpms and debs
- Linux distributions including CentOS, Ubuntu, SLES, RedHat, and Fedora
- Ansible
- Docker
- Xen
- KVM
- C/C++ toolchains including cross-compilation, automake/autoconf, cmake, and meson
- Parallel programming
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 Compute CUDA Quality Assurance team for NVIDIA's Enterprise SWQA release schedules. Are you passionate about 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 automation team, you will 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 5+ years testing SW development cycle.
Solid understanding of embedded systems, Linux, Python, C and C++.
Experience with cloud infrastructure is a big plus
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 along with hardware and software components that enable cloud computing services.
Ways to stand out from the crowd:
Expertise in packaging software in Linux (rpms, debs) and knowledge in Linux distribution (Centos, Ubuntu, SLES, RedHat, Fedora)
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)
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
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant people on the planet working for us. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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.
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.