AI/ML Memory Performance Intern: Traces & Bottlenecks

Micron; San Jose (CA); On-site; USD 69,000 - 77,000; Full time

Job summary

Micron Technology is seeking an AI/ML Workload Analysis Intern to collaborate with system architects and performance engineers on analyzing AI workloads and evaluating next-generation computing and memory architectures. You will develop methodologies to characterize memory behavior, generate workload traces, and identify bottlenecks across AI training and inference applications.

You will work with real-world AI workloads, trace collection tools, and analytics frameworks to understand memory

Qualifications

• Pursuing an MS or PhD in Computer Engineering, Computer Science, Electrical Engineering, Data Science, or a related field.
• Coursework or research experience in Computer Architecture, ML/DL, Parallel Computing, OS, Data Structures & Algorithms, Performance Analysis.
• Programming experience in Python and C/C++.
• Strong analytical, problem-solving, and quantitative reasoning skills.
• Excellent written and verbal communication skills.

Responsibilities

• Analyze AI/ML workloads including LLMs, recommendation models, vision, multimodal and generative AI applications.
• Collect, process, and analyze memory traces from AI training and inference workloads.
• Characterize memory access patterns, locality, reuse, bandwidth utilization, and latency sensitivity.
• Characterize compute, memory, storage, and interconnect behavior across AI training and inference workloads.
• Develop workload traces, performance models, and architecture simulation environments.
• Investigate system bottlenecks related to memory capacity, bandwidth, latency, cache utilization, and communication overheads.
• Evaluate architectural tradeoffs across CPUs, GPUs, NPUs, accelerators, and memory technologies.
• Create automation frameworks for workload execution, data collection, and results analysis.
• Validate simulation and analytical models using benchmark and hardware measurements.
• Present findings through technical reports, visualizations, and architecture reviews.

Skills

Python

C/C++

Analytical thinking

Communication

Education

MS/PhD in CS

Tools

Nsight

VTune

Perf

Gem5

Accel-Sim

Job description

Micron Technology is seeking an AI/ML Workload Analysis Intern to collaborate with system architects and performance engineers on analyzing AI workloads and evaluating next-generation computing and memory architectures. You will develop methodologies to characterize memory behavior, generate workload traces, and identify bottlenecks across AI training and inference applications.

You will work with real-world AI workloads, trace collection tools, and analytics frameworks to understand memory