College Grad - Memory System Architect, HBM Generative AI

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

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.

• 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.

• 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, Tensor Flow, 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.

• 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:

$ - $ a year

Additional compensation may include benefits, bonuses and equity.
Our salary ranges are determined by role, level, and location.

The range displayed on each job posting…