Intern - AI Hardware and Memory Systems

Job Title

Intern - AI Hardware and Memory Systems

Role Summary

Join the HBM Architecture team to research and prototype memory and system architecture concepts for next-generation AI accelerators and high-performance computing platforms. Work focuses on performance modeling, workload analysis, and evaluating memory hierarchy and interconnect design impacts on system performance and power efficiency.

This internship provides hands-on research experience collaborating with architects and engineers to influence future AI infrastructure.

Experience Level

Intern (PhD level). Entry-level: 0–2 years of relevant research or internship experience.

Responsibilities

Key responsibilities include architecture research, modeling, workload analysis, and cross-functional collaboration.

• Research and evaluate memory and system architecture concepts for AI accelerators (GPUs, TPUs, custom designs).
• Develop and analyze performance models for bandwidth, latency, power, scalability, and overall system efficiency.
• Analyze AI training, inference, and HPC workloads to identify memory and system performance bottlenecks.
• Investigate optimizations across memory hierarchy (HBM, DRAM, caches), storage, and interconnects.
• Collaborate with cross-functional engineering teams and explore AI/LLM-based tools to support research workflows.

Requirements

Must-have technical skills and experience for this PhD internship.

• 0–2 years of relevant experience through research, internships, academic projects, or industry work.
• Knowledge of memory system architecture: caches, HBM, DRAM, memory hierarchy, and interconnect concepts.
• Experience with performance modeling, architectural simulation, or system analysis.
• Programming experience in Python, C++, or similar languages.
• Strong analytical, problem-solving, and technical communication skills.

Nice-to-have:

• Research experience with AI accelerators, GPU architecture, interconnects, or high-performance computing.
• Experience with AI/ML frameworks (PyTorch, TensorFlow) or CUDA-based development.
• Familiarity with architectural simulators, SystemC, GPU profiling tools, emulation platforms, or performance analysis tools.
• Knowledge of rack-scale systems, scale-up/scale-out architectures, and advanced interconnect technologies.
• Publications or demonstrated research contributions in computer architecture, AI hardware, or memory systems.

Education Requirements

Currently pursuing a PhD in Computer Architecture, Electrical Engineering, Computer Engineering, Computer Science, or a related technical field. PhD candidacy is explicitly required for this internship.

About the Company

Company: Micron Technology

Headquarters: Boise, Idaho, USA

Micron Technology is a global leader in memory and storage solutions, dedicated to transforming how the world uses information. The company offers a diverse portfolio of high-performance DRAM, NAND, and NOR memory products under the Micron and Crucial brands. With a commitment to customer focus and technological innovation, Micron drives advancements in artificial intelligence, 5G, and other data-centric applications, empowering users to learn, communicate, and progress.