HBM Design Architect Intern – AI-Driven Memory Innovation

1000 Micron Technology, Inc.; Richardson (TX); On-site; USD 26,000 - 38,000; Full time

Benefits offered by this job

Medical, Dental, Vision plans

Paid time off

Paid holidays

Job summary

Micron Technology, Inc. is seeking an HBM Design Architect Intern to work with senior architects and engineers evaluating HBM and DRAM concepts, building analytical models, and exploring design tradeoffs affecting performance, power, and reliability.

You will apply AI-assisted engineering workflows, including LLMs and generative AI, to support design exploration, data analysis, and productivity while collaborating across architecture, circuit, layout, and product teams.

Qualifications

• Must be pursuing a graduate degree (MS/PhD) and returning to the program after internship.
• Strong foundation in CMOS, digital/mixed-signal design, memory systems, or related areas.
• Experience with engineering analysis, modeling, or simulation through coursework, research, or internships.

Responsibilities

• Analyze HBM/DRAM architecture tradeoffs for timing, bandwidth, power, area, and thermal performance.
• Develop first‑order models, simulations, and data‑analysis tools to compare design options.
• Collaborate with architecture, circuit, layout, and product teams to assess feasibility and tradeoffs.
• Review simulations and silicon data to validate assumptions and propose evidence‑based recommendations.
• Apply LLMs and Generative AI to enhance analysis and productivity and document findings for multi‑functional teams.

Skills

CMOS circuits

Digital design

Memory systems

Thermal sciences

Power delivery

Signal integrity

Advanced packaging

Education

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

Tools

HSPICE

FineSim

Spectre

Job description

Micron Technology, Inc. is seeking an HBM Design Architect Intern to work with senior architects and engineers evaluating HBM and DRAM concepts, building analytical models, and exploring design tradeoffs affecting performance, power, and reliability.

You will apply AI-assisted engineering workflows, including LLMs and generative AI, to support design exploration, data analysis, and productivity while collaborating across architecture, circuit, layout, and product teams.