Intern - Machine Learning Engineering

Micron Technology • Richardson, TX

3d

About The Position

Micron Technology is a world leader in memory and storage solutions. The Storage and Memory Systems (SMS) Pathfinding team explores future memory and storage technologies for 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 for future computing platforms and memory solutions.

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

Requirements

• Have 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 pursue a Bachelor's, Master's, or PhD degree in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field.
• Have a strong understanding of computer architecture, machine learning, artificial intelligence, or high-performance computing concepts.
• Have experience with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, JAX, or similar technologies.
• Demonstrate strong analytical, problem-solving, communication, and collaboration skills.

Nice To Haves

• 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.

Responsibilities

• Research emerging AI models, workloads, and computing architectures to understand future memory and storage requirements.
• Analyze performance, power, cost, bandwidth, capacity, latency, and scalability tradeoffs 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.

Benefits

• Choice of medical, dental, and vision plans.
• Programs to help protect income in the event of illness or injury.
• Paid family leave.
• Paid time off.
• Paid holidays.

What This Job Offers

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