Intern Memory Systems Architecture & AI Accelerators

Develop rigorous experimental methodologies for end-to-end workload evaluation Build research prototypes in software and/or FPGA-based hardware Perform quantitative analysis to explain observed performance behavior Contribute to internal research artifacts and potential publications Currently enrolled in a PhD program in Computer Engineering, Electrical Engineering, or Computer Science. Intern cannot graduate prior to September 2026. Strong background in computer architecture and memory systems Experience with systems programming (C/C++ and/or low-level Python) Demonstrated interest in research and experimental systems work Comfortable reading and understanding research papers and low-level code Prior research in memory systems, GPUs, or accelerators Experience with FPGA development (RTL or HLS) Familiarity with performance modeling, profiling, or simulation Coursework or publications in architecture or systems