Memory System Architect New Grad - HBM Generative AI

The HBM Architecture team defines the future of memory systems that enable next-generation AI, machine learning, and high-performance computing applications. By researching advanced memory architectures, system designs, and emerging technologies, the team develops innovative solutions that maximize performance, scalability, and efficiency for future memory products. As a Memory System Architect on the HBM Architecture team, you will contribute to the definition of future memory architectures supporting Generative AI and data-intensive workloads. You will research and evaluate advanced memory system concepts, analyze AI accelerator architectures, and develop models that guide product strategy and technology roadmaps for next-generation memory solutions. ## Responsibilities - Research and evaluate advanced memory architecture concepts for AI accelerators, including GPU, TPU, and emerging compute platforms. - Develop and analyze system-level models to assess performance, power, scalability, and efficiency across memory and compute architectures. - Investigate memory hierarchy optimizations involving HBM, DRAM, cache, storage, and interconnect technologies. - Evaluate architectural trade-offs and emerging technologies, including compute-near-memory concepts, to support future product development. - Collaborate with cross-functional teams to translate research findings into architecture recommendations and long-term technology roadmaps. ## Minimum Qualifications - 0-2 years of relevant experience through research, internships, academic projects, publications, or industry experience in computer architecture, memory systems, AI hardware, or high-performance computing. - Master's degree, PhD, or equivalent experience in Computer Architecture, Electrical Engineering, Computer Engineering, Computer Science, or a related technical field. - Strong understanding of GPU, TPU, AI accelerator, or large-scale computing architectures. - Knowledge of memory hierarchy concepts, including caches, HBM, DRAM, storage systems, and memory performance optimization. - Experience with performance modeling, architectural simulation, system analysis, or related research methodologies. - Programming experience in Python, C++, and/or AI computing frameworks such as CUDA, TensorFlow, or similar technologies. - Strong analytical, problem-solving, communication, and collaboration skills. - Familiarity with AI-enabled tools and large language models (LLMs) such as Copilot, Claude, or similar technologies. ## Preferred Qualifications - Research experience in AI accelerators, computer architecture, memory systems, high-performance computing, or large-scale distributed systems. - Experience with compute-near-memory, processing-in-memory, or advanced memory architecture concepts. - Publications, conference presentations, patents, or demonstrated technical contributions in relevant research areas. - Familiarity with industry-standard memory technologies, interfaces, and protocols. - Experience developing architectural roadmaps, technology strategies, or long-term product planning recommendations. - Knowledge of rack-scale systems, AI infrastructure, networking, or large-scale training and inference environments.The US base salary range that Micron Technology estimates it could pay for this full-time position is $103,000.00 - $210,000.00 a year. Additional compensation may include benefits, bonuses and equity.