Intern – AI & Electrical Engineering (LLM / Agent Systems)
About The Position
Monolithic Power Systems, Inc. (MPS) is one of the fastest growing companies in the Semiconductor industry. We are worldwide technical leaders in Integrated Power Semiconductors and Systems Power delivery architectures. At MPS, we cultivate creativity, are passionate about sustainability, and are committed to providing leading-edge products and innovation to our customers. Our portfolio of technology helps power our world ---come join our team and see how YOU can make a difference. Job Description: We are seeking an Electrical Engineering (EE) and Computer Science (CS) intern to support the development of next-generation AI systems focused on power electronics and semiconductor products. You will be contributing to the creation of intelligent agents that assist engineers and customers with product discovery, design decisions, and technical analysis. Interns will work on fine-tuning large language models (LLMs), building RAG datasets, and structuring engineering knowledge into AI-ready formats.
Requirements
- Currently pursuing a degree in: Electrical Engineering, Computer Science, or related field
- Coursework or experience in Power Electronics and Machine Learning
- Familiarity with Python libraries (Pandas, NumPy, etc.), LLM concepts (fine-tuning, RAG, embeddings), and database systems
Responsibilities
- AI Model Development & Evaluation Assist in fine-tuning LLMs using EE-focused datasets (datasheets, application notes, technical docs) Develop and execute evaluation frameworks for model performance Create test cases and benchmarks for engineering-specific Q&A and reasoning Analyze model outputs and identify gaps in technical accuracy
- AI dataset creation and optimization Extract and optimize RAG datasets using data from datasheets, application notes, and other technical documentation and sources.
- AI Agent Development Contribute to the design and testing of AI agents (e.g., FAE assistant, product selector) Help define agent workflows, prompts, and tool usage Support integration of: Vector databases (semantic search) Parametric search (SQL-based filtering) Improve agent reasoning for engineering use cases
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
Number of Employees
501-1,000 employees
