NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by phenomenal technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. Doing what’s never been done before takes vision, innovation, and the world’s best talent. We are now looking for Design Automation Tool development Engineers for our Tegra SOC development group. As the Lead, you will be responsible for architecting and crafting end-end tool flow to auto-generate system fabrics, sub-systems and SOC hierarchies, keeping user interface, maintainability and scalability in mind.
One should possess Strong software development skills and a dedication to high quality work. A proven track record to conceptualize, design and implement modular and robust EDA tools with well thought out APIs and interfaces would make you an excellent fit. Having a deep understanding of object oriented programming is a prerequisite for this role. If you have a zeal to make things better, we will have an excellent match for our needs.
What you’ll be doing:
Define next gen EDA workflows for the world's top chip designers and verification engineers.
Architect and develop tools, methodologies that bring AI in chip design cycle.
Analyze productivity bottlenecks, improve data analytics and visualizations of day-to-day workflows
Debug interesting, complex, and important problems that impact the team
What we need to see:
BS/MS in Computer Science or Computer Engineering or Electrical Engineering or equivalent experience
2+ years of relevant work experience
Strong problem-solving abilities and a passion for debugging
Software architecture, development, & testing experience
Solid understanding of Linux and excellent coding skills (Perl/Python)
Excellent communication and interpersonal skills
Ways to stand out from the crowd:
Exposure to RTL design/verification tools (VCS or equivalent simulation tools, debug tools like Verdi) and methodologies (UVM or equivalent)
Experience implementing scalable infrastructure solutions with frontend UX, RESTful APIs, database, visualization, and backend automation.
Experience in deploying ML components in various stages of tool.
Linux administration experience, revision control and CI/CD systems such as Jenkins
#LI-Hybrid
Skills Required
- Bachelor’s or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience
- 2+ years of relevant work experience
- Strong problem-solving abilities and passion for debugging
- Software architecture, development, and testing experience
- Solid understanding of Linux
- Excellent coding skills in Perl or Python
- Excellent communication and interpersonal skills
- Exposure to RTL design and verification tools such as VCS or Verdi, and methodologies such as UVM
- Experience implementing scalable infrastructure with frontend UX, RESTful APIs, databases, visualization, and backend automation
- Experience deploying machine learning components in tools
- Linux administration experience
- Experience with revision control and CI/CD systems such as Jenkins
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.
NVIDIA Insights
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.”
