Intern - Machine Learning Engineering

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.

Department Overview

The Storage and Memory Systems (SMS) Pathfinding team explores future memory and storage technologies that enable next-generation AI, high-performance computing, and data-centric systems. By studying emerging AI workloads, system architectures, and memory technologies, the team helps define innovations that shape the future of computing platforms and memory solutions.

Position Overview

As an intern in the Storage and Memory Systems (SMS) Pathfinding team, you will research emerging AI workloads, evaluate future memory and storage architectures, and analyze how evolving system requirements impact next-generation technologies. You will collaborate with architects, researchers, and engineers to model, benchmark, and assess innovative concepts that influence Micron's long-term memory and storage roadmap.

Responsibilities

• Research emerging AI models, workloads, and computing architectures to understand future memory and storage requirements.
• Analyze tradeoffs between performance, power, cost, bandwidth, capacity, latency, and scalability across AI systems.
• Develop models, simulations, benchmarks, and analytical tools to evaluate next-generation memory and storage concepts.
• Characterize AI workloads running on CPUs, GPUs, accelerators, and memory-centric computing platforms.
• Collaborate with architects and engineers to assess new technologies, communicate findings, and support proof-of-concept evaluations.

Minimum Qualifications

• 0-2 years of relevant experience through internships, research projects, academic coursework, or technical projects in computer architecture, AI/ML, high-performance computing, or memory systems.
• Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field.
• Strong understanding of computer architecture, machine learning, artificial intelligence, or high-performance computing concepts.
• Experience with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, JAX, or similar technologies.
• Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Knowledge of memory systems, caching, memory hierarchies, DRAM technologies, and system performance bottlenecks.
• Experience with performance analysis, benchmarking, profiling, simulation, or system modeling methodologies.