VLSI Timing Methodology Intern - Summer 2027

NVIDIA is hiring a VLSI Timing Methodology Intern - Summer 2027 in Santa Clara, United States. It pays $20-$94/hr and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this role Little AI ●○○○: aI is not part of the work.
Level classifies it as an internship.
Level lists 2,700+ other open roles at NVIDIA.
The role was posted in the last few days.

AI in this role

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.

If you enjoy combining multiple interests across VLSI design, device modeling, Static timing Analysis, software development, accelerated computing and AI, you’ll love the kind of work we do. Our team combines advances in both high-performance software and VLSI hardware design to craft large scale internal CAD tools and silicon projection methodologies for delivering outstanding computing hardware. If you are passionate about innovation in these areas, let’s talk about many possible projects.

What you’ll be doing:

Research and develop compact device and system models to predict silicon, both time-0 and aged, timing behavior in pre-silicon simulation world
Use Machine Learning and analytical techniques to speed up device and system timing characterization.
Develop tools, and methodologies to predict and improve silicon performance and reliability beyond what industry standard tools can offer alone.
Explore how physical effects (e.g., IR drop, crosstalk, aging, thermal impact) influence timing and design decisions.

What we need to see:

Currently enrolled and pursuing a Master's degree or higher in Electrical Engineer, Computer Engineering, or related field.
Knowledge in digital circuit design , MOSFET device physics and Static Timing Analysis.
Experience in VLSI backend design.
Good understanding of Machine Learning and statistics.
Shown knowledge or experience with scripting in Python, Perl, or Tcl.

Ways to stand out from the crowd:

Prior VLSI working experience or internships is a plus.
Familiarity with BSIM or other device compact models.
Coursework or academic projects in VLSI Design or CAD Design.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We encourage you join our team with some of the most hard-working people in the world working together to promote rapid growth. Are you passionate about becoming a part of an outstanding team supporting the latest in GPU and AI technology? If so, 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 expected hourly rate for this position is 20 USD – 94 USD.

You will also be eligible for Intern benefits.

Applications for this job will be accepted at least until November 8, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

How we rate this

VLSI Timing Methodology Intern - Summer 2027 at NVIDIA rates 12 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.