Intern, AI Memory Architecture & Performance Modeling

1000 Micron Technology, Inc.; Richardson (TX); On-site; USD 34,000 - 48,000; Full time

Benefits offered by this job

Medical, dental, vision

Paid time off

Holiday leave

Job summary

Micron Technology seeks an HBM Design Architecture Intern in Richardson, TX. This role offers hands-on exposure to AI system trends and memory subsystem analysis while working closely with senior engineers and mentors.

You will assist with performance modeling, tool development, and the refinement of simulation frameworks used to model AI cluster performance and memory behavior. Minimum qualifications include pursuing a Master’s or PhD in Electrical or Computer Engineering or Computer Science,

Qualifications

• Pursuing a Master’s or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Must be able to work onsite for 6 months and cannot graduate before the end of the internship.
• Foundational understanding of computer architecture, digital systems, and hardware/software interaction.
• Programming experience in Python, C/C++, or similar languages.

Responsibilities

• Research AI compute, networking, and storage trends to understand future workloads.
• Support HBM architecture analysis by gathering bandwidth, latency, and memory requirements data.
• Help develop or refine simulation frameworks modeling AI cluster performance and memory behavior.
• Participate in building trend dashboards using CSP benchmarks and industry datasets.
• Collaborate with mentors to explore architectural opportunities for next‑gen AI systems.

Skills

Python

C/C++

Hardware knowledge

Data analysis

Education

Master’s degree

PhD

Tools

Simulation tools

Job description

Micron Technology seeks an HBM Design Architecture Intern in Richardson, TX. This role offers hands-on exposure to AI system trends and memory subsystem analysis while working closely with senior engineers and mentors.

You will assist with performance modeling, tool development, and the refinement of simulation frameworks used to model AI cluster performance and memory behavior. Minimum qualifications include pursuing a Master’s or PhD in Electrical or Computer Engineering or Computer Science,