Intern - Compute System Compatibility Engineer

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.

We validate Micron memory products on current and next-generation computing platforms. As an Intern System Compatibility Engineer, you will join our System Enablement and Test Development teams and gain hands-on experience with platform bring-up, system configuration, memory validation, test development, automation, data analysis, and AI-enabled engineering workflows under the guidance of experienced engineers.

We will provide technical mentorship, structured onboarding, and exposure to DRAM, BIOS and firmware interactions, computer architecture, laboratory workflows, responsible use of approved AI tools, and the memory product lifecycle from initial bring-up through qualification and readiness.

Key Responsibilities

• Set up and support Intel, AMD, and ARM-based systems in Linux, Windows, and UEFI environments; document hardware, BIOS, firmware, operating system, memory, and test configurations for repeatable execution and traceability.
• Implement memory validation activities that assess compatibility, stability, reliability, performance, and platform readiness.
• Reproduce and triage failures, collect logs and diagnostic data, use issue-tracking systems, apply structured failure-analysis methods, and support validation of corrective actions.
• Build or refine automation using Python, PowerShell, C++, or related languages; use approved AI-assisted tools to accelerate code development, test generation, log analysis, data summarization, technical research, documentation, and reporting while applying engineering judgment to verify accuracy and results.
• Apply responsible AI practices by protecting confidential information, using company-approved tools and data sources, documenting AI-assisted work where appropriate, identifying potential errors or bias, and independently validating generated code, analysis, and technical conclusions before use.
• Collaborate with System Enablement, Test Engineering, product, quality, and program teams on assigned validation and root-cause investigation activities.
• Communicate findings, risks, dependencies, corrective actions, and recommended next steps through concise documentation and presentations.
• Internship Assignment - The intern will complete a bounded technical project or workstream with defined milestones, measurable deliverables, technical documentation, and a final presentation. The assignment will be selected to provide relevant business value while remaining achievable within a three-month summer internship.

Required Qualifications

• Currently pursuing a bachelor's or graduate degree in Computer Engineering, Electrical Engineering, Computer Science, or a closely related technical field. Must be continuing education in the fall term following the internship; the expected graduation date must not be before September of the same year.
• Foundational knowledge of computer hardware, operating systems, computer architecture, and structured problem-solving.
• Programming or scripting experience gained through coursework, projects, laboratories, student organizations, or other technical experience using Python, PowerShell, C++, or a comparable language.
• Basic proficiency using AI-enabled tools to research technical topics, develop or solve code, analyze data, summarize findings, or improve documentation, with the ability to review outputs critically and confirm accuracy.
• Ability to follow test procedures, maintain accurate configuration records, analyze data, and summarize technical results. Interest in hands-on laboratory validation, system debug, test development, or engineering automation.

Preferred Qualifications

• Experience working with DRAM, memory systems, BIOS or UEFI, firmware, server or client platforms, or hardware interfaces.
• Familiarity with x86 or ARM architectures, Intel, AMD, ARM-based, or embedded platforms, and Linux, Windows, or UEFI environments.
• Experience with oscilloscopes, logic analyzers, protocol analyzers, power measurement equipment, or similar diagnostic tools.
• Experience applying generative AI, machine learning, automation, or data-analysis tools to an engineering or academic workflow, for example developing code, generating tests, analyzing logs, identifying patterns, creating dashboards, improving documentation, or automating repetitive tasks.
• Clear written and verbal communication, attention to detail, adaptability, partnership, and willingness to learn unfamiliar tools and technologies.