Senior SWQA Test Development Engineer

Reposted One Month Ago
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Santa Clara, CA, USA
In-Office
168K-322K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Drive end-to-end quality in AI microservices, lead testing strategies, mentor engineers, and enhance automation practices while validating AI inference workflows.
Summary Generated by Built In

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 September 4, 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.

Skills Required

  • BS or higher degree in CS/EE/CE majors
  • 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 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

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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