Senior Software Development Engineer in Test - SDET

at Nvidia

📍 Santa Clara, United States

USD 140,000-270,200 per year

SENIOR

✅ On-site

Tech Stack
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.

AI @ 4 Docker @ 4 GPU @ 4 Kubernetes @ 4 LLM Linux @ 6 OpenStack @ 4 Parallel Programming @ 6 Python @ 7

Details

At NVIDIA, the team in Santa Clara, California is seeking a Senior Software Engineer in Test to work on AI and accelerated computing technologies, including NVIDIA enterprise offerings such as NIM, NeMo, and BioNeMo.

Responsibilities

Execute test cases to validate NVIDIA enterprise offerings, including NIM, NeMo, and BioNeMo.
Create, implement, and maintain automated test cases and supporting automation infrastructure.
Collaborate with development teams to triage issues, perform root cause analysis, verify fixes, define additional tests, and improve test plans.
Investigate and apply AI capabilities to accelerate the quality assurance process.

Requirements

Master's or PhD degree in computer science or a relevant field, or equivalent experience.
At least 5 years of professional experience in software testing.
Proficiency in written and spoken English.
Comfort working with Linux.
Strong shell and Python programming skills.
Strong knowledge of quality assurance principles and software testing.
Experience using AI development tools to create test plans, develop test cases, and automate test cases.
Excellent problem-solving abilities.
Strong interpersonal skills, quick learning ability, a proactive approach, innovation, and dedication.
Self-motivation and a passion for learning new technologies.
Knowledge of large language models and AI models is a plus.

Additional Qualifications

Experience working with NVIDIA GPU hardware.
Background in parallel programming.
Experience with virtualization technologies such as Docker, Kubernetes, and OpenStack.

Benefits

Equity and employee benefits are provided.
Applications will be accepted at least until June 14, 2026.
NVIDIA is an equal opportunity employer committed to an inclusive work environment.