AI-Driven Physical Design Engineering (PhD Intern)

Intel Corporation; Fort Collins (CO); On-site; USD 142,000 - 143,000; Part time

Job summary

Intel Corporation in Santa Clara, CA invites a PhD intern to join its AI-driven physical design team. You will help develop AI-powered workflows for silicon implementation and intelligent data analysis to optimize PPA and execution efficiency.

The role emphasizes collaboration across the Data Center Group, building dashboards and ML-powered tools using Python, TCL, and industry-standard EDA flows to advance design quality.

Qualifications

• Enrolled in a PhD program in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Proficiency in industry-standard tools for physical design, including synthesis, place and route, and timing analysis software.
• Familiarity with scripting languages like Python or TCL for flow automation and debugging.
• Understanding of digital design concepts and methodologies, including RTL design and verification.

Responsibilities

• Research and implement AI/ML techniques to identify new opportunities for improving physical design processes and methodologies.
• Develop AI-enhanced workflows for high-performance silicon implementation that reduce manual effort and improve design quality.
• Build ML-powered data analysis and summarization pipelines to enable faster, more accurate design decision-making.
• Design and implement Graph Neural Network (GNN) based systems to support dynamic, intelligent decision-making in design execution.
• Develop intelligent automation frameworks using Python, and ML libraries such as TensorFlow or PyTorch, alongside traditional scripting in TCL and Perl.
• Collaborate with cross-functional AI research and design engineering teams to align AI-driven strategies with broader project objectives.
• Evaluate and benchmark AI-driven methodologies against traditional approaches to demonstrate measurable improvements in PPA (Power, Performance, Area).

Skills

Python programming

Graph Neural Networks (GNNs)

Data analysis (Pandas/NumPy/Matplotlib

Reinforcement learning concepts

EDA tools and physical design

Education

PhD student in Electrical Engineering, Computer Engineering, or Computer Science

Tools

Synthesis tools

Place-and-route tools

Timing analysis software

Job description

The Role And Impact

Intel is seeking motivated individuals to join its dynamic design engineering team as an AI-Driven Physical Design Engineering PhD Intern. This role offers a unique opportunity to leverage artificial intelligence and machine learning techniques to revolutionize the physical implementation of cutting-edge silicon designs. You will focus on developing AI-powered workflows, building intelligent data analysis capabilities, and designing adaptive systems that enhance execution efficiency and optimize implementation strategies through data-driven decision making.

Job Details

Job Description:

The Role And Impact

Intel is seeking motivated individuals to join its dynamic design engineering team as an AI-Driven Physical Design Engineering PhD Intern. This role offers a unique opportunity to leverage artificial intelligence and machine learning techniques to revolutionize the physical implementation of cutting-edge silicon designs. You will focus on developing AI-powered workflows, building intelligent data analysis capabilities, and designing adaptive systems that enhance execution efficiency and optimize implementation strategies through data-driven decision making.

Business Group

The Data Center Group (DCG) is at the forefront of developing high-performance computing solutions that power the world’s data-centric applications. This team is dedicated to designing innovative silicon technologies that support Intel’s mission to lead in processing, storage, and networking solutions for data centers. Join a group committed to shaping the future of technology by solving complex challenges and driving performance enhancements.

Key Responsibilities

• Research and implement AI/ML techniques to identify new opportunities for improving physical design processes and methodologies.
• Develop AI-enhanced workflows for high-performance silicon implementation that reduce manual effort and improve design quality.
• Build ML-powered data analysis and summarization pipelines to enable faster, more accurate design decision-making.
• Design and implement Graph Neural Network (GNN) based systems to support dynamic, intelligent decision-making in design execution.
• Develop intelligent automation frameworks using Python, and ML libraries such as TensorFlow or PyTorch, alongside traditional scripting in TCL and Perl.
• Collaborate with cross-functional AI research and design engineering teams to align AI-driven strategies with broader project objectives.
• Evaluate and benchmark AI-driven methodologies against traditional approaches to demonstrate measurable improvements in PPA (Power, Performance, Area).

Minimum Qualifications

• Enrolled in a PhD program in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Proficiency in industry-standard tools for physical design, including synthesis, place and route, and timing analysis software.
• Familiarity with scripting languages like Python or TCL for flow automation and debugging.
• Understanding of digital design concepts and methodologies, including RTL design and verification.

Preferred Qualifications

• Strong problem-solving skills with a creative and innovative mindset.
• Ability to work effectively in a collaborative, team-oriented environment.
• Exceptional organizational and communication skills to drive alignment across diverse teams.
• Understanding of Graph Neural Networks (GNNs) or graph-based algorithms
• Experience with data analysis tools (Pandas, NumPy, Matplotlib)
• Knowledge of reinforcement learning concepts for design optimization
• Strong Python programming skills with ML application experience
• Background in EDA tools and physical design fundamentals

Job Type

Student / Intern

Shift

Shift 1 (United States of America)

Primary Location

US, California, Santa Clara

Additional Locations

US, Colorado, Fort Collins, US, Massachusetts, Beaver Brook, US, Oregon, Hillsboro, US, Texas, Austin

Posting Statement

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $141,998.00 - 142,002.00 USD

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Our standard internship rates are based on your degree, location, and the job role. Your recruiter can share more about the specific compensation range for your preferred location and job role during the hiring process.

Work Model for this Role

This role will require an on-site presence. Job posting details (such as work model, location or time type) are subject to change. The application window for this job posting is expected to end by 02/09/2027