[Hiring] Intern - Memory & System Architecture Research @Micron Technology

Role Description

We are seeking a Memory & System Architecture Research Intern with a strong computer-architecture and systems-modeling background to characterize AI workloads and help build and validate performance models for advanced memory systems. You will translate AI workload trends into memory capacity, bandwidth, and latency requirements, and quantify architectural tradeoffs to inform long-term technology and product direction. This role suits a graduate or Ph.D. student who is comfortable in ambiguous problem spaces and enjoys turning hypotheses into quantified, published evidence. Applying Artificial Intelligence is expected as part of this position.

Key Responsibilities

• Workload characterization: Analyze AI training and inference workloads to derive memory bandwidth, capacity, and latency requirements.
• System modeling: Contribute to analytical and simulation models that evaluate memory-centric system architectures at scale.
• Architecture studies: Assess system-level tradeoffs across emerging memory and integration technologies.
• Validation & accuracy: Benchmark models against reference data to improve accuracy and ensure reproducible results.
• Quantified analysis: Produce system-level performance, efficiency, and cost analyses that inform architectural decisions.
• Documentation & publishing: Capture findings in internal technical reports and contribute to invention disclosures where applicable.

Qualifications

• Currently pursuing an M.S. or Ph.D. in Computer Architecture, Computer Engineering, Electrical Engineering, or a related field.
• Strong background in computer architecture and system-level performance analysis (memory hierarchy, bandwidth, latency, scaling).
• Ability to analyze complex memory and AI performance challenges and reason about tradeoffs quantitatively.
• Proficiency in Python for building analytical models and performance analysis.
• Good verbal and written communication and problem-solving abilities.

Requirements

• Understanding of memory architectures (HBM, DDR, LPDDR, CXL, emerging memories) and their impact on AI/ML workloads.
• Understanding of near-memory and advanced integration technologies — 3D stacking, chiplets, interposers, heterogeneous packaging — and their system-level tradeoffs.
• Experience with AI systems and accelerators (GPU/ASIC), performance benchmarking, or design-space exploration.
• Familiarity with simulation frameworks and reproducible experimentation.

Benefits

• Choice of medical, dental and vision plans in all locations.
• Benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave.
• Robust paid time-off program and paid holidays.