AI-Driven Physical Design Engineering (PhD Intern)

Intel Corporation; Santa Clara (CA); On-site; USD 142,000 - 143,000; Full time

Benefits offered by this job

On-site internship

Job summary

Intel Corporation seeks PhD interns in Electrical/Computer Engineering or CS to advance AI-driven physical design. You will research AI/ML methods, build AI-enhanced workflows, and develop data-analysis pipelines to guide design decisions and optimize PPA.

on-site in Santa Clara, with opportunities across US locations. The role emphasizes collaboration with cross-functional AI and design teams, strong scripting in Python/TCL, and applying GNNs to dynamic design problems while measuring

Qualifications

• Enrolled in a PhD program in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Proficiency with industry-standard physical design tools (synthesis, place & route, timing analysis).
• Scripting with Python or TCL for flows and debugging.
• Understanding of RTL and digital design concepts.

Responsibilities

• Research and implement AI/ML techniques to identify opportunities for improving physical design processes.
• Develop AI-enhanced workflows for high-performance silicon implementation.
• Build ML-powered data analysis and summarization pipelines for faster design decisions.
• Design and implement Graph Neural Network (GNN) based systems for intelligent design execution.
• Develop automation frameworks using Python and ML libraries (TensorFlow, PyTorch) with TCL/Perl scripting.
• Collaborate with AI research and design teams to align AI strategies with project goals.
• Evaluate AI-driven methods against traditional approaches to demonstrate improvements in PPA.

Skills

Python

TCL

ML/AI

Pandas/NumPy

Education

PhD student in Electrical/Computer Engineering or CS

Tools

Synthesis tools

Place & Route tools

Timing analysis software

Job description

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).

Qualifications

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.

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.
• Annual Salary Range for jobs which could be performed in the US: $141,998.00-142,002.00 USD.
• Work Model for this Role: This role will require an on-site presence.
• 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.

Our Commitment

Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

Application Window

The application window for this job posting is expected to end by 02/09/2027.