Senior Software Development Engineer in Test, Confidential Computing - SDET
at Nvidia
USD 168,000-270,200 per year
Used Tools & Technologies
Not specified
Required 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.
Security @ 7
Software Development @ 4
Ansible @ 4
Docker @ 4
Linux @ 4
Python @ 4
Parallel Programming @ 4
QA @ 7
Agile @ 4
CUDA @ 4
GPU @ 4
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 Confidential Computing team on NVIDIA's Enterprise SWQA team. The role focuses on feature development, automation, test and validation infrastructure, and using AI tools to aid in solving complex issues. You will develop large-scale systems running hundreds of tests per day across distributed, heterogeneous servers with NVIDIA GPUs to verify multiple designs and configurations in automation farms or in the cloud.
Responsibilities
- Develop test plans and orchestrate testing for compute software releases on new compute architecture platforms (including Tesla GPUs, NVIDIA turnkey systems and OEM systems).
- Design and implement automation frameworks and infrastructure for testbench-independent test specification and execution workflows used by worldwide chip validation teams.
- Build and operate large-scale automation systems running many tests per day across distributed heterogeneous servers and GPU resources.
- Incorporate advanced AI tools to enhance testing capabilities, streamline operations, and improve test coverage and reliability.
- Improve code coverage and develop roadmaps that prioritize software development schedules across the full lifecycle: tool development, test, and deployment.
- Collaborate with cross-functional teams to identify features, lead developers in definition, automation implementation, and productization of features.
- Lead automation of manual test cases and develop automation support, working closely with automation infrastructure teams.
- Focus on improving customer experience by enhancing usability and performance.
- Test software functionality, internal code/structure, and run regression tests for existing CUDA/driver features.
- Work in a dynamic agile software development team with high production quality standards.
Requirements
- BS or MS in Engineering (or equivalent experience) with 8+ years of experience in the software testing/development cycle.
- Solid understanding of embedded systems, Linux, Python, C and C++.
- Proven experience using AI tools for automation and test plan development applied to daily tasks.
- Strong technical skills with deep understanding of orchestration & automation systems, data centers, and cloud architecture.
- Solid QA methodology knowledge and strong attention to detail.
- Knowledge of cluster and cluster management.
- Experience developing test strategies, high-quality test plans, and executing tests.
- Proficient in building test setups and fine-tuning hardware and software test environments.
- Experience or strong interest in platform security, cloud infrastructure, and highly regulated deployment environments.
Ways to stand out
- Expertise in embedded system feature development and knowledge of both software and hardware stacks.
- Experience applying AI-powered tools to improve test efficiency and quality (test case/plan/script generation, defect detection, automated bug fixing, etc.).
- Experience with configuration and deployment management (Ansible), containers (Docker) and virtualization (Xen, KVM, Hyper-V).
- Good understanding of C/C++ toolchains on Linux including cross-compilation, automake/autoconf, CMake, Meson.
- Background with parallel programming, ideally CUDA C/C++ and OpenACC.
Compensation & Benefits
- Base salary range: 168,000 USD - 270,250 USD (determined by location, experience, and market pay).
- Eligible for equity and employee benefits (see NVIDIA benefits).
Other
- Applications accepted at least until July 6, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.