VLSI CAD Timing Intern, Applied AI - Summer 2027

Job Title

VLSI CAD Timing Intern, Applied AI - Summer 2027

Role Summary

Internship to develop end-to-end solutions for timing and constraint analysis workflows, including data generation, model training, orchestration, and automation. The role sits on a cross-disciplinary CAD/physical-design/methodology team building systems that learn from sign-off data and help engineers achieve faster, more predictable timing closure.

Experience Level

Internship - entry-level (Summer 2027). Intended for students in graduate programs; see Education Requirements for details.

Responsibilities

Primary responsibilities include:

• Support and learn static timing analysis (STA) flows using tools such as PrimeTime and Tempus.
• Develop and automate timing, constraints, and QoR validation flows using scripting and data-driven methods.
• Analyze 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 AI- or analytics-assisted approaches for timing analysis, constraint checking, and flow optimization.
• Investigate how physical effects (IR drop, crosstalk, aging, thermal) influence timing and design decisions.

Requirements

Core technical skills and experiences required or strongly preferred.

Must-have

• Coursework or academic knowledge in VLSI/ASIC design, digital circuits, or computer architecture.
• Familiarity with static timing analysis concepts, constraints, or digital design flows.
• Programming/scripting skills (Python preferred).
• Ability to work with data and timing reports and to solve technical problems in complex systems.
• Exposure to applying agentic AI to back-end VLSI tasks (e.g., floorplanning, timing closure, physical verification).

Nice-to-have

• Academic projects, research, or internships related to VLSI, physical design, STA, or EDA tools.
• Exposure to TCL scripting.
• Experience with machine learning, data analysis, or AI concepts applied to engineering problems.
• Experience automating workflows or analyzing large datasets.

Education Requirements

Currently pursuing a Master’s or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Relevant coursework in VLSI/ASIC design, digital circuits, or computer architecture is expected. (No alternate "equivalent experience" language specified.)

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.