Intern – Memory Systems Architecture & AI

What you'll do

• Research tiered memory architectures and memory hierarchy optimizations for AI inference and large language model workloads.
• Develop models, simulations, and prototypes; analyze memory performance, data movement, and workload behavior.
• Evaluate architectural trade-offs and document and present findings in collaboration with architecture teams.

What they ask for

• 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.
• Systems programming experience with C++, Python, or similar languages, and familiarity with performance evaluation methods.
• 0–2 years of relevant experience through research, publications, internships, academic projects, or experimental systems research.

Nice to have

• Research or development experience in memory systems, AI accelerators, GPUs, inference systems, or HPC; relevant publications or presentations.
• Experience with simulators, workload characterization, FPGA/RTL/HLS, or AI workloads such as LLMs and MoE.

Pay

$49.85 - $49.85 an hour USD (base salary)

Tools

C++, Python, Claude, Copilot, FPGA, RTL, High-Level Synthesis (HLS)

AI focus

Research memory architectures and optimizations for AI inference and LLM workloads, including workload analysis, memory management, and system performance evaluation. Requires experience using AI-enabled tools and LLMs to support research or engineering workflows.