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Intern - Computer Engineer, AI/LLM at Micron Technology

Boise, Idaho, United States -

Full Time

Start Date

Immediate

Expiry Date

27 Mar, 26

Salary

0.0

Posted On

27 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AI/ML, EDA Automation, Predictive Analytics, Design Optimization, CAD Software, Unix/Linux, Shell Scripting, TensorFlow, PyTorch, SKILL, C, C++, Java, Perl, Lisp

Industry

Semiconductor Manufacturing

Description

Innovate to develop tools, flows, and methodologies that increase efficiency and reliability of memory designs. Apply AI/ML techniques to improve EDA automation, predictive analytics, and design optimization. Explore LLM‑based agentic workflows for intelligent tool orchestration, documentation generation, and design assistance. Design and develop CAD software and AI‑enabled automation flows; assess architecture and hardware limitations for ML integration. Provide training, documentation, and support to end‑users on new tools and methods. Collaborate closely with build and process teams to integrate technology-based solutions into production flows. Bachelor's degree (Graduation date should not be prior to September 1, 2026) or equivalent experience in Computer Engineering or Computer Science with circuits/VLSI coursework, or other degrees with relevant proven experience. Excellent programming fundamentals; in‑depth Python experience preferred. Strong interest or experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and LLM‑based applications (e.g., Claude Code, ChromaDB, MCP development). Experience with Unix/Linux and shell scripting. Good communication and problem‑solving skills. Familiarity with SKILL, C, C++, Java, Perl, or Lisp. Knowledge of data engineering and model deployment (pipelines, inferencing, observability). Experience defining and implementing agentic systems that harness LLMs for intelligent design assistance. Exposure to semiconductor EDA environments and design flows.

Responsibilities

Develop tools and methodologies to enhance memory design efficiency and reliability. Collaborate with teams to integrate technology solutions into production flows.