SMS Pathfinding Engineering Intern

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 Storage and Memory Systems (SMS) Pathfinding team explores next-generation memory, storage, and interconnect technologies that will enable future AI, cloud, and high-performance computing systems. The team evaluates emerging architectures, advanced memory solutions, and innovative technologies to help shape Micron's long-term product strategy and technology roadmap.

As an intern in the Storage and Memory Systems (SMS) Pathfinding group, you will research photonic interconnect technologies that enable disaggregated memory architectures for future AI systems. You will develop modeling and analysis tools to evaluate silicon photonic memory fabrics, assess system-level tradeoffs, and explore how optical interconnects can improve memory capacity, latency, bandwidth, energy efficiency, and scalability for next-generation AI workloads.

• Develop parameterized photonic link budget and system-level models to evaluate optical memory fabrics, including lasers, modulators, wave guides, switches, photodetectors, and interconnect architectures.
• Analyze performance, latency, bandwidth, power efficiency, reliability, and scalability tradeoffs across photonic memory architectures and memory technologies such as HBM, DDR5, and LPDDR.
• Evaluate protocol and system-level impacts of CXL-based memory expansion and disaggregated memory architectures for AI workloads.
• Utilize AI-enabled tools and technologies to improve productivity, data analysis, technical problem solving, documentation, and decision-making.
• Calibrate and validate models using industry data, proof-of-concept platforms, simulations, and available measurement results.
• Collaborate with architects, researchers, and industry partners to communicate findings through technical reports, white papers, presentations, and architecture recommendations.

• 0-2 years of relevant experience through research, internships, academic projects, publications, or coursework in photonics, optical interconnects, computer architecture, memory systems, or related fields.
• Currently pursuing a Master's or PhD degree in Electrical Engineering, Computer Engineering, Photonics, Optics, Applied Physics, or a related technical discipline.
• Coursework or research experience in silicon photonics, integrated optical devices, computer architecture, memory systems, interconnects, or system design.
• Proficiency in Python and scientific computing tools for modeling, simulation, and data analysis.
• Strong analytical, communication, presentation, and collaborative problem-solving skills.

• Experience with photonic link budget analysis, optical transceivers, optical communications, or photonic system modeling.
• Familiarity with CXL, PCIe, memory fabrics, memory expansion architectures, or large-scale system interconnects.
• Experience with photonic simulation tools such as Lumerical, GDSFactory, MEEP, SAX, Simphony, or similar platforms.
• Knowledge of AI infrastructure, AI inference workloads, GPU memory systems, memory pooling, or large language model architectures.
• Publications, research contributions, or hands‑on experience involving photonic systems, optical networks, memory architectures, hardware characterization, or experimental validation.

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