Intern

About the Role

The DRAM Systems & Architecture Lab researches next-generation memory architectures for future AI, machine learning, and high-performance computing systems. This role offers the opportunity to contribute to research that may influence future product roadmaps, publications, and advanced memory system designs.

Key Responsibilities

• 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.

Requirements & Tech Stack

• 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.

Qualifications

• 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.