The Chip Design Methodologies team is responsible for establishing ASIC design methodologies, developing shared code, providing design guidance, and driving the adoption of new technologies. The team plays a key role in ensuring chip design teams operate efficiently and adhere to best practices. We are now expanding our focus to AI-powered applications for chip design — leveraging modern AI tools and methods to improve productivity, quality, and turnaround across the design flow. This role offers an exciting opportunity to think innovatively and make a significant impact within a dynamic, technology-focused organization.
What You'll Be Doing:
Develop innovative AI-powered methodologies and applications for chip design — spanning specification, RTL, verification, and physical design
Collaborate with chip design stakeholders across architecture, RTL, DV, FV, and physical design teams to understand existing challenges and form the best solutions
Utilize, develop, and assimilate AI-based tools and flows into the chip design process
Evaluate cutting-edge AI tools and EDA vendor technologies, and apply them to improve the development process
Define and enforce design quality standards — lint rules, synthesis guidelines, and coding best practices
Develop training sessions and guide designers with best design practices, including AI-assisted workflows
Build automation infrastructure and scripted flows to streamline chip design development
What We Need To See:
BSc degree in Electrical Engineering
10+ years hands-on pre silicon design experience
Strong interpersonal skills, a passion for innovation, and the ability to mentor
A natural drive to systematize, automate, and improve how things are done
Strong AI orientation — genuine curiosity about AI-driven development, with a working understanding of the modern AI ecosystem: AI coding assistants, agentic workflows, and prompt-driven engineering practices
Ways To Stand Out From The Crowd:
Wide system level understanding of the chip design development and flows
Strong interpersonal skills
Passion for innovation, quality, efficiency and flows automation
Chip design experience combined with hands-on AI tool usage - you've used AI to solve real engineering problems
Experience with CI/CD for hardware development (Git, GitLab, or equivalent)
NVIDIA is widely considered to be one of the technology world’s most desirable employers and has been ranked Israel’s most desirable employer for two consecutive years (2024-2025), reflecting our culture of innovation and excellence, and people-first values. Are you a creative and autonomous engineer who loves a challenge? Come join our networking chip design team and help us developing great products by bringing innovation and raising the efficiency and the quality standard in the team.
Skills Required
- BSc degree in Electrical Engineering
- 10+ years hands-on pre silicon design experience
- Strong AI orientation with understanding of AI-driven development
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.”
