Architecture Intern - MS

## Your Team, Your Impact Group Description Join the architecture team within Marvell’s Custom Cloud Solutions group to help shape next-generation storage and memory architectures for AI data centers. Your work will influence how cutting-edge AI workloads access and process data at scale. Marvell is a leading supplier of storage and memory controller solutions for the AI data center. You’ll gain hands-on experience in cutting-edge AI infrastructure, collaborate with industry experts, and contribute to innovations shaping the future of data centers. ## What You Can Expect - Gain a deep understanding of storage and memory systems in the AI data center - Research the role of data storage and memory devices in AI data processing pipelines - Explore how storage and memory hierarchies impact large-scale AI training and inference - Collaborate with engineers and architects to define system and chip architectures for AI storage and memory solutions - Develop performance models for simulations using C/C++ or Python to evaluate architectural trade-offs. - Analyze chip and system architectures based on performance, latency, and cost metrics - Identify optimal hardware/software partitioning for future storage and memory controllers - Prepare architecture presentations and specifications; present findings to the team - Work with cross-functional teams to share insights and leverage capabilities ## What We're Looking For - Currently pursuing a Master’s Degree in Electrical Engineering, Computer Engineering, or a related field with an expected graduation date between Fall 2027 – Summer 2028 - Coursework or research experience in computer architecture, hardware design, programming, and modeling techniques - Understanding of AI training and inference algorithms, including large language models and transformer architectures - Strong analytical and problem-solving skills - Ability to work collaboratively in dynamic environments - Excellent verbal and written communication skills - Passion for learning and working in a fast-paced environment ## Preferred Qualifications: - Knowledge of system architectures for data centers and AI workloads - Familiarity with modern interconnects (PCIe, NVMe, CXL), memory/storage technologies (NAND, DRAM, SSDs), and processor architectures (CPUs and GPUs) - Strong programming skills in C, C++ or Python - Experience with performance analysis tools or architectural simulators