Intern – Memory Systems Architecture & AI

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. The DRAM Systems & Architecture Lab researches next-generation memory architectures that enable future AI, machine learning, and high-performance computing systems.

The team explores innovative memory technologies, system architectures, and hardware-software co-design approaches to improve performance, scalability, and efficiency for emerging AI workloads. As a Research Intern in the DRAM Systems & Architecture Lab, you will conduct research focused on next-generation memory systems for AI accelerators. You will investigate tiered memory architectures, analyze AI workload behavior, develop experimental prototypes, and evaluate architectural innovations across hardware, software, and system-level environments.

This role offers the opportunity to contribute to research that may influence future product roadmaps, publications, and advanced memory system designs.

• Research and evaluate tiered memory architectures designed to improve performance and scalability for AI inference and large language model workloads.
• Develop experimental methodologies, models, simulations, and prototypes to analyze memory system performance, data movement, and workload behavior.
• Investigate memory hierarchy optimizations, data placement strategies, cache management, and memory migration mechanisms across AI computing systems.
• Perform quantitative analysis using hardware platforms, simulation environments, and FPGA-based prototypes to evaluate architectural trade-offs.
• Document research findings, present technical results, and collaborate with architecture teams to contribute to future technology strategies and research initiatives.

• 0-2 years of relevant experience through PhD research, publications, internships, academic projects, or experimental systems research in computer architecture, memory systems, AI accelerators, or high-performance computing.
• Currently pursuing a PhD in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field.
• Strong understanding of computer architecture, memory hierarchy design, and system performance analysis.
• Experience with systems programming using C++, Python, or similar programming languages.
• Familiarity with performance modeling, simulation, profiling, benchmarking, or experimental system evaluation methodologies.
• Strong analytical, problem-solving, and technical communication skills.
• Experience using AI-enabled tools and large language models (LLMs), such as Claude, Copilot, or similar technologies to support research, development, or engineering workflows.
• Ability to work independently while collaborating effectively within a research-focused team environment.

• Research experience in memory systems, AI accelerators, GPUs, large-scale inference systems, or high-performance computing architectures.
• Experience developing architectural simulators, analytical models, workload characterization frameworks, or system performance evaluation tools.
• Familiarity with AI inference workloads, large language models, KV cache management, Mixture-of-Experts (MoE) architectures, or memory‑centric AI system design.
• Experience with FPGA development, RTL design, High-Level Synthesis (HLS), or hardware prototyping platforms.
• Peer‑reviewed publications, conference presentations, patents, or other demonstrated research contributions in computer architecture or systems research.
• Experience working across hardware,…