AI Engineering Intern at Littelfuse in Chicago

Summary: Littelfuse is a leading global manufacturer of electronic components, recognized as one of America’s Best Mid-Sized Companies. They are seeking an AI Engineering Intern to work on implementing AI systems, focusing on large language models and advanced Retrieval-Augmented Generation pipelines while collaborating with cross-functional teams. Responsibilities: - Contribute to new features, user interface/experience enhancements, integrations, and tool/function-calling capabilities under team guidance - Help design, implement, and optimize end-to-end RAG pipelines, including data ingestion, chunking, embedding generation, vector storage, retrieval, and post-processing - Evaluate and benchmark system performance, mitigate hallucinations, and document resulting improvements - Monitor emerging developments in LLMs, RAG systems, agentic workflows, and AI tools - Conduct experiments, analyze results, document findings, and deliver weekly insights and recommendations to the team Required Qualifications: - Currently pursuing a Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, or a closely related field (rising juniors, seniors, or recent graduates preferred) - Strong proficiency in Python 3.11+ with hands-on experience - Familiarity with Git, Docker, and Linux/WSL environments - Solid understanding of LLMs, prompt engineering, embeddings, and vector databases - Excellent problem-solving abilities, documentation skills, and verbal/written communication - Proven ability to collaborate effectively in cross-functional teams and with diverse stakeholders Preferred Qualifications: - Prior hands-on experience with local LLMs, RAG systems, or open-source AI tooling - Experience with FastAPI, PostgreSQL, or cloud platforms (Azure, GCP, AWS) - Prior research experience, including reading academic papers and conducting experiments - Deep passion for Artificial Intelligence field of study Required Skills: Python 3.11+, LLMs, RAG pipelines Important Skills: Git, Docker, Linux/WSL, FastAPI, PostgreSQL, cloud platforms