Senior Software Test Development Engineer - Deep Learning

Reposted 2 Days Ago
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Santa Clara, CA, USA
In-Office
140K-270K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves automating tests, developing test cases, and ensuring product quality for NVIDIA's Deep Learning software across various applications.
Summary Generated by Built In

We are looking for a Software Test development engineer in NVIDIA’s Deep Learning SWQA team. The position is in NVIDIA Deep Learning and AI Software Quality Assurance team that defines, develops and performs tests to validate robustness and measure the performance of NVIDIA‘s Deep Learning software and GPU Infrastructure for autonomous driving, healthcare, speech recognition, natural language processing, and a wide variety of other AI scenarios. We collaborate with multiple AI product teams to develop new products; derive and improve complex test plans; and improve our workflow processes for a diverse range of GPU computing platforms.

You should grow with being in the critical path supporting developers working for billion-dollar business lines as well as intimately understanding the values of responsiveness, thoroughness and collaboration. You should constantly champion and implement efficiency improvements across your domain. Join the team which is building software which will be used by the entire world!

What you’ll be doing:

  • Work closely with global multi-functional teams to understand the test requirements and take ownership of product quality.

  • Plan/design/implement/report/automate test plan/test case/test reports.

  • Run bug lifecycle and co-work with inter-groups to work towards solutions.

  • Automate test cases and assist in the architecture, crafting and implementing of test frameworks.

  • In-house repro and verify customer issues/fixes.

What we need to see:

  • BS or higher in CS/EE/CE or equivalent experience.

  • 6+ years of software quality assurance or test automation background with knowledge of test infrastructure and strong analysis skills.

  • Scripting language (Python, Perl, Bash) knowledge and UNIX/Linux experience.

  • Good C/C++ software development or test development experience.

  • Good user/development experiences of virtualization like VM & Docker container.

  • Understanding and working knowledge with any Deep Learning Framework and models especially in end-to-end customer scenarios.

  • Experience in validating Deep Learning software and Deep Learning models.

  • Experience in using AI development tools for test plans creation, test cases development and test cases automation.

  • Able to balance conflicting/changing priorities and maintain a positive attitude while experiencing ambitious and dynamic schedules.

  • Excellent English written and oral communication skills.

Ways to stand out from the crowd:

  • Familiarity with NVIDIA GPU hardware products (Tesla, Tegra, DGX, etc.); working knowledge of NVIDIA GPU Computing (CUDA) and CUDA libraries for Deep Learning.

  • Background in building models and AI-based infrastructure to improve test automation.

  • Experience with LLM inference frameworks (TRT-LLM, vLLM, SGLang, etc.) and familiar with running various AI workloads

  • Background in validating Data Center GPU based infrastructure (multi-GPUS, multi-nodes, cluster).

  • Experience in VectorCAST, Bullseye, Gcov, or Coverity tools.

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.

Applications for this job will be accepted at least until March 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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.

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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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