Intern - HBM Design Architect | MS or PhD Student

Micron Technology; Richardson (TX); On-site; USD 28,000 - 55,000; Full time

Job summary

Micron Technology is seeking an HBM Design Architect Intern to assess HBM and DRAM architecture concepts, build analytical models, and study design tradeoffs affecting performance, power, and manufacturability. You will work with senior architects and engineers, leveraging AI tools to support design exploration and productivity.

The internship offers hands-on semiconductor architecture exposure and collaboration across architecture, design, verification, packaging, and product teams, with

Qualifications

• Pursuing a Master’s or Ph.D. in EE/CE and planning to return to the degree program.
• Strong foundation in multiple areas listed above (core semiconductor topics).
• Experience with engineering analysis, modeling, or simulation tools.
• Excellent problem-solving and communication skills.

Responsibilities

• Analyze HBM and DRAM architecture tradeoffs related to timing, bandwidth, power, area, thermal performance, reliability, and design complexity using analytical, simulation, and AI Assisted methodologies.
• Develop first‑order models, simulations, and data‑analysis tools to compare design alternatives, identify key sensitivities, and support architecture pathfinding studies.
• Collaborate with architecture, circuit design, verification, layout, packaging, product, and system engineering teams to evaluate implementation feasibility and technology tradeoffs.
• Review simulation, experimental, and silicon data to perform root‑cause analysis, validate assumptions, improve model accuracy, and develop evidence‑based recommendations.
• Apply Large Language Models (LLMs), Generative AI, and AI Assisted engineering workflows to enhance engineering analysis, technical research, and productivity while documenting and presenting findings to multi‑functional teams.

Skills

CMOS circuits

digital/mixed-signal design

semiconductor devices

computer architecture

memory systems

thermal sciences

power delivery

signal integrity

advanced packaging

Education

Master’s or Ph.D. in Electrical Engineering or Computer Engineering or related field

Tools

HSPICE

FineSim

Spectre

Job description

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

About The Team

At Micron Technology, we transform how the world uses information to enrich life for all. The Heterogeneous Integration Group (HIG) HBM Architecture team develops next-generation High-Bandwidth Memory (HBM) solutions that enable advancements in Artificial Intelligence, high-performance computing, networking, and data center technologies. The team collaborates across architecture, design, verification, packaging, product engineering, and system engineering to evaluate innovative memory technologies and drive future product development.

Position Overview

As an HBM Design Architect Intern, you will work alongside experienced architects and engineers to evaluate HBM and DRAM architecture concepts, develop analytical models, and investigate design tradeoffs affecting performance, power, thermal behavior, reliability, and manufacturability. This internship provides hands‑on experience in semiconductor architecture analysis while offering opportunities to leverage AI Assisted engineering workflows, Large Language Models (LLMs), and Generative AI technologies to support design exploration and engineering productivity.

Responsibilities

• Analyze HBM and DRAM architecture tradeoffs related to timing, bandwidth, power, area, thermal performance, reliability, and design complexity using analytical, simulation, and AI Assisted methodologies.
• Develop first‑order models, simulations, and data‑analysis tools to compare design alternatives, identify key sensitivities, and support architecture pathfinding studies.
• Collaborate with architecture, circuit design, verification, layout, packaging, product, and system engineering teams to evaluate implementation feasibility and technology tradeoffs.
• Review simulation, experimental, and silicon data to perform root‑cause analysis, validate assumptions, improve model accuracy, and develop evidence‑based recommendations.
• Apply Large Language Models (LLMs), Generative AI, and AI Assisted engineering workflows to enhance engineering analysis, technical research, and productivity while documenting and presenting findings to multi‑functional teams.

Minimum Qualifications

• Currently pursuing a Master's or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field and returning to the degree program following completion of the internship.
• Strong academic foundation in at least two of the following areas: CMOS circuits, digital or mixed‑signal design, semiconductor devices, computer architecture, memory systems, thermal sciences, power delivery, signal integrity, or advanced packaging.
• Experience using engineering analysis, modeling, or simulation tools through graduate research, coursework, laboratory projects, or internships.
• Demonstrated ability to define assumptions, perform technical analysis, evaluate results, and communicate evidence‑based conclusions.
• Strong problem‑solving, analytical, written communication, and verbal communication skills.

Preferred Qualifications

• Graduate research, internship, thesis, dissertation, or project experience related to HBM, DRAM, SRAM, memory controllers, high‑speed interfaces, semiconductor architecture, or 3D integrated circuit technologies.
• Experience with transistor‑level simulation or schematic‑entry tools such as HSPICE, FineSim, Spectre, or similar platforms.
• Understanding of timing, power, area, performance, thermal, and reliability tradeoffs in advanced semiconductor products.
• Familiarity with AI workloads and the impact of memory bandwidth, latency, capacity, power, and thermal characteristics on system performance.
• Experience using data analytics, Large Language Models (LLMs), Generative AI, or AI Assisted engineering workflows to improve technical insight, design exploration, or productivity.

As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time‑off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on micron.com/careers/benefits.

Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.

To learn more about Micron, please visit micron.com/careers

For US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron’s People Organization at [e-mail] or 1-800-336-8918 (select option #3)

Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards.

Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron.

AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification.