Intern - Machine Learning Engineering

About the Role

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.

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.
• Familiarity with GPU computing, accelerators, heterogeneous computing systems, or AI infrastructure.
• Understanding of AI model architectures, training workflows, inference systems, and workload characterization techniques.
• Experience applying AI-enabled tools and technologies to research, software development, data analysis, or engineering productivity workflows.

Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.