AI-Assisted Memory Design Intern

The role

This intern will work with the foundation IP team to explore AI-assisted and self-adaptive memory design techniques. The role focuses on leveraging operating-condition awareness to optimize memory operation for performance, power efficiency, and yield.

What you will do

• Analyze conventional memory assist techniques and explore AI/ML-driven optimization for control logic and supply modulation.
• Investigate AI/ML-based techniques to analyze memory operating conditions and predict robustness.
• Explore self-timed, self-adaptive, and intelligent memory techniques.
• Develop AI/ML-assisted monitoring, prediction, and adaptive control techniques.
• Document, benchmark, and present the proposed self-adaptive memory architecture and design insights.

Required qualifications

• Pursuing a BS in EE, CE, Microelectronics, or related field (rising Junior/Senior)
• Coursework in Digital Integrated Circuits, Analog Circuit Design, VLSI Design, or Semiconductor Devices
• Coursework in Machine Learning, Optimization, Data Analytics, Computational Methods or related courses
• Basic understanding of CMOS circuit design and IC layout (DRC/LVS) concepts
• Working knowledge of Python and basic ML concepts (regression, clustering)
• Comfort working with large datasets
• Strong analytical and problem-solving ability

Nice to have

• Exposure to layout/schematic tools (Virtuoso, Calibre) or characterization tools (SiliconSmart, PrimeTime, Liberate)
• Interest in low-power IP for edge AI/IoT
• Strong passion, eagerness, and curiosity to learn and explore transistor-level circuit design

About the company

Ambiq is on a mission to enable intelligence everywhere by powering the AI edge revolution with low-power semiconductor solutions. Since 2010, they have shipped over 300 million units to customers building wearables, medical devices, IoT products, and AI-powered edge applications.