As a Machine Learning for Physical Design Intern, you'll contribute to advancing chip implementation workflows by creating intelligent tools that optimize key metrics such as performance, power, and area. Based in Santa Clara, you'll work within a team focused on solving complex challenges in physical design using machine learning techniques.
What You'll Do
- Design and implement machine learning models to accelerate chip design cycles and improve PPA outcomes from synthesis through tapeout
- Collaborate with physical design engineers to integrate ML into critical stages including place and route, timing closure, and power grid analysis
- Choose and prepare relevant datasets, selecting effective data representations for training and inference
- Develop and refine custom ML algorithms suited to the unique constraints of hardware design flows
- Run experiments, analyze results statistically, and iteratively enhance model accuracy and performance
What We're Looking For
- Enrollment in a BS, MS, or PhD program in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field
- Solid foundation in mathematics, probability, statistics, and algorithm design
- Proven ability to apply machine learning to real-world technical problems
- Strong programming skills in Python and C/C++, with experience in data structures and software development
- Experience building ML-driven solutions for improving design efficiency and turnaround time
- Ability to conduct testing, interpret data, and refine models based on empirical feedback
Technology Environment
You'll work with Python, C++, and modern ML frameworks, applying them to tasks in physical design, synthesis, place and route, timing analysis, and power grid modeling. Familiarity with RISC-V architectures is a plus.
Work Environment
This is a hybrid role requiring four days per week on-site in Santa Clara with one remote day. You'll gain direct exposure to core aspects of ASIC implementation while working alongside seasoned engineers in synthesis, timing, and physical design domains.
Compensation & Benefits
Pay ranges from $50 to $70 per hour, with actual offers depending on experience, education, technical background, and location. The company is committed to equal opportunity hiring and provides meaningful hands-on experience in cutting-edge AI hardware development. Note: Employment is subject to U.S. export control regulations, which may require specific citizenship, residency status, or licensing for access to controlled technology.
