VLSI Design Automation Intern, Applied AI - Summer 2026 job opportunity at NVIDIA.

Home Jobs In United States Of America Tag: Applied AI - Summer 2026 VLSI Design Automation Intern, Applied AI - Summer 2026 position at NVIDIA


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NVIDIA VLSI Design Automation Intern, Applied AI - Summer 2026
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Applied AI - Summer 2026

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loacation US, CA, Santa Clara, United States Of America
loacation US, CA, Santa ..........United States Of America

NVIDIA has continuously reinvented itself over two decades. Our 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. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to resolve, that only we can seek, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence. We are looking for a VLSI CAD Timing Intern focused on Applied AI to lead end-to-end solution development — spanning data generation, model training, orchestration, and agentic automation — for timing and constraint analysis workflows. You will be part of a cross-disciplinary team building intelligent systems that learn from sign-off data, reason across flows, and assist engineers in achieving faster and more predictable closure. What You’ll Be Doing: Learn and support static timing analysis (STA) flows using industry tools like PrimeTime and Tempus for advanced ASIC designs. Help develop and automate timing, constraints, and QoR validation flows using scripting and data-driven methods. Assist with analyzing timing reports, constraints, and design data across corners and modes to improve closure predictability. Collaborate with CAD, physical design, and methodology engineers on timing sign-off strategies and best practices. Contribute to early AI- or analytics-assisted approaches for timing analysis, constraint checking, or flow optimization. Explore how physical effects (e.g., IR drop, crosstalk, aging, thermal impact) influence timing and design decisions. What we need to see: Currently pursuing a Master's or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Exposure to Applied Agentic AI. Coursework or academic knowledge in VLSI/ASIC design, digital circuits, or computer architecture. Familiarity with the basics of static timing analysis, constraints, or digital design flows. Knowledge in scripting or programming (Python preferred). Comfort working with data, reports, and technical problem-solving in complex systems. Ways to stand out from the crowd: Academic projects, research, or internships related to VLSI, physical design, STA, or EDA tools. Exposure to machine learning, data analysis, or AI concepts applied to engineering problems. Exposure to TCL. Experience automating workflows, analyzing large datasets, or contributing to technical tools or open-source projects. NVIDIA is widely considered one of the technology world’s most desirable employers. We employ some of the most forward-thinking and talented people in the world. Are you passionate about joining our life work to amplify human creativity and intelligence? If you are creative, collaborative, and have a real passion for design methodology and automation, we want to hear from you. Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.
 You will also be eligible for Intern   benefits . ​ Applications for this job will be accepted at least until January 13, 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.

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