New College Grad - Memory System Architect, HBM Generative AI

Micron Technology • Folsom, CA

1d • $103,000 - $210,000 • Onsite

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

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.

Benefits

• Choice of medical, dental and vision plans
• Benefit programs that help protect your income if you are unable to work due to illness or injury
• Paid family leave
• Robust paid time-off program
• Paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level