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Senior SWQA Test Development Engineer

NVIDIA Corporation

US, CA, Santa ClaraPosted Aug 31, 2026
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Skills named in this posting

  • Python
NVIDIA is the world leader in accelerated computing and AI. Our technologies power the most advanced AI platforms, including NeMo microservices and NVIDIA Inference Microservices (NIM), enabling scalable, production‑grade AI deployment across cloud and enterprise environments. We are looking for a senior, technically strong test development engineer to drive quality, automation, and technical leadership in this rapidly evolving space. What You’ll Be Doing: • Own and drive end‑to‑end quality from design through release and production readiness • Lead test strategy, planning, and execution across functional, integration, system, performance, and reliability testing • Design, build, and maintain test frameworks and automation for microservice‑based, containerized AI systems • Provide technical leadership and mentorship to less senior engineers including guiding test design, automation practices, and quality standards • Partner closely with cross functional teams to influence architecture and improve testability • Validate LLM and AI inference workflows, including model lifecycle, APIs, CLIs, deployment configurations, and scaling scenarios • Drive defect triage, root‑cause analysis, and quality metrics, ensuring issues are addressed systematically and efficiently • Leverage AI‑assisted testing techniques to improve coverage, efficiency, and signal‑to‑noise in test results What We Need to See: • BS or higher degree in CS/EE/CE majors (or equivalent experience) • 8+ years of experience in software development, test development, or quality engineering roles • Strong proficiency in Python and test automation frameworks • Experience testing distributed systems, microservices, or cloud‑native platforms • Solid understanding of Linux, Docker, Kubernetes, and CI/CD pipelines • Proven ability to lead technically, review designs, and mentor other engineers • Strong debugging skills and ability to reason about complex, system‑level failures • Excellent communication skills and experience working across geographically distributed teams Ways to Stand Out from the Crowd: • Experience testing AI/ML platforms, LLM pipelines, or inference services • Hands‑on exposure to NeMo, NIM, or model‑as‑a‑service platforms • Experience with performance, scale, and reliability testing in production‑like environments • Applying AI tools to enhance test development, automation, and diagnostics • Prior ownership of quality for customer‑facing or production‑critical services At NVIDIA, quality is foundational. This role offers the opportunity to set the quality bar for NVIDIA’s next‑generation AI microservices, influence architecture, and lead others—while working alongside some of the best engineers in the industry. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until July 12, 2026. 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.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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