Intern - SSD Architecture Modeling
Listed on 2026-10-11
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Software Development
AI Engineer (Applied/Software), Software Engineer, Python
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 Architecture Modeling team develops software, modeling platforms, and analytical tools that enable the evaluation and optimization of next-generation storage system architectures. By combining simulation, data analytics, automation, and AI-enabled engineering practices, the team helps accelerate architectural decision-making and improve engineering productivity across product development organizations.
As an Architecture Modeling Intern, you will develop software tools and automation solutions that support architecture modeling, simulation analysis, and performance characterization efforts. You will collaborate with architects, firmware engineers, and systems engineers to analyze complex datasets, identify performance bottlenecks, improve engineering workflows, and leverage AI technologies to enhance productivity and technical decision‑making.
Responsibilities- Develop software tools and automation solutions for architecture modeling, simulation analysis, and performance characterization activities.
- Create workflows to process, analyze, visualize, and report on large engineering datasets to improve insight generation and decision-making.
- Design dashboards, reporting tools, and analytics solutions that improve engineering productivity and identify performance trends or anomalies.
- Apply AI-assisted development techniques, automation frameworks, and intelligent analytics to accelerate software development and engineering workflows.
- Collaborate with cross-functional engineering teams to solve technical challenges, support validation activities, and improve modeling and simulation methodologies.
- 0-2 years of relevant experience through internships, research projects, academic coursework, software development projects, or engineering experience in computer architecture, systems software, data analytics, modeling, simulation, or related fields.
- Currently pursuing a Master’s, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or a related technical field.
- Proficiency in Python, C++, or similar programming languages.
- Strong understanding of software development fundamentals, data structures, algorithms, and debugging techniques.
- Experience working in Linux or Unix development environments.
- Strong analytical, problem-solving, and technical communication skills.
- Demonstrated ability to leverage AI-enabled tools and technologies, including large language models (LLMs) such as Copilot, Claude, ChatGPT, or similar platforms, to improve productivity, learning, software development, and problem-solving.
- Experience with modeling, simulation, performance analysis, benchmarking, or data analytics tools.
- Knowledge of computer architecture, storage systems, distributed systems, systems software, or performance engineering concepts.
- Familiarity with data visualization frameworks, machine learning techniques, or AI-assisted software development tools.
- Experience with Git, automated testing frameworks, CI/CD pipelines, or workflow automation.
- Interest in applying artificial intelligence, machine learning, generative AI, or intelligent analytics to improve engineering workflows and technical decision‑making.
- Strong written and verbal communication skills with the ability to present technical findings to engineering stakeholders.
- Experience developing production-quality software tools, dashboards, analytics platforms, or…
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