We are looking for a Hardware Tools Application Engineer who will serve as the primary interface between our internal customers and the development team. Our group develops software solutions for various internal teams within the company, and our users include chip designers, algorithm engineers, PHY characterization engineers, optics engineers, and more. The role involves not only resolving technical issues but also understanding the broader needs of these engineering teams, contributing new ideas, and helping to design and develop tools that improve their workflow and productivity.
What you’ll be doing:
Provide technical support to internal engineering teams, helping diagnose and resolve issues across diverse areas such as hardware, software, and Linux environments.
Debug, solve, and analyze problems effectively, ensuring minimal disruption for engineering workflows.
Understand customer needs (chip design, algorithm development, PHY and optics characterization, etc.) and translate them into product improvements or new tools.
Collaborate closely with software developers to enhance existing solutions and design new internal tools.
Communicate findings, solutions, and technical insights effectively to both customers and the development team.
Collect, analyze, and summarize customer feedback to drive continuous improvements.
What We Need To See:
B.Sc in Electrical Engineering.
4+ years of relevant experience.
Excellent debugging skills — ability to investigate, analyze, and resolve complex issues across software, hardware, and system layers.
Proficiency in Python.
Experience with post-silicon (Post-Si) hardware work and lab instrumentation, hands-on with tools such as real-time/sampling oscilloscopes, spectrum analyzers.
Strong communication skills and ability to collaborate with multi-functional engineering groups.
Fluency in English for technical and professional communication.
Familiarity with both software and hardware domains
Ways to stand out from the crowd:
Knowledge of object-oriented programming (OOP) and design patterns
Experience in developing support automation tools or internal utilities.
Knowledge of DevOps, CI/CD, or containerized environments.
Strong knowledge of hardware, particularly SerDes and Optics
NVIDIA has some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. We are 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.
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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.
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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.
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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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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.”
