UIUC Research Park Intern - ML AI Motor Controls Algorithm - Rivian

Internship Term: Fall 2026

Rivian internships are experiences optimized for student candidates. To be eligible, you must be an undergraduate or graduate student in an accredited program during the internship term with an expected graduation date between December 2026 through May 2028. Rivian's Internship Program requires active student enrollment.

Information regarding your expected degree completion date is collected solely to verify eligibility and determine your availability for future full-time opportunities. Rivian is an equal opportunity employer and does not use graduation dates to determine the age of applicants or as a basis for discriminatory hiring decisions.

If you are not pursuing a degree, please see our full time positions on our Rivian careers site.

Note that if your university has specific

requirements

for internship programs, it is your responsibility to fulfill those

requirements

.

In this role, you will help develop an integrated analytical workflow that leverages Cloud infrastructure and Large Language Models (LLMs), alongside traditional machine learning, to derive actionable insights from complex vehicle data. The project's main focus is architecting an automated, cloud-connected system for high-level data preparation and analysis.

• Data & Feature Engineering: Design and implement robust Python-based tools to parse, decode, and extract features from automotive PCAP logs.
• Signal Processing: Apply advanced signal-processing techniques to transform vehicle data and perform large-scale analysis of corner cases of interest.
• ML Model Building: Research, develop, and train machine learning models (e.g., Decision Trees, Random Forests, Neural Networks) for prediction, detection, and classification tasks.
• System Integration: Architect the end-to-end workflow that processes raw vehicle logs, performs automated analysis, and prepares data for model training.
• Data visualization: Create easy-to-understand dashboards for the general audience, focusing clearly on outcomes to support decision making.
• Must be currently pursuing a masters or PhD degree at the University of Illinois Urbana Champaign (PhD

preferred

)

• Actively pursuing a degree or one closely related in Computer Science, Computer Engineering, Electrical Engineering, or Physics
• Proficiency in AI practices and feeding LLM with data and knowledge base
• Strong Programming Fluency: Expertise in Python (including Pandas, NumPy, Scikit-learn) for data analysis and modeling.
• Advanced ML Knowledge: Deep theoretical and practical understanding of classification algorithms (e.g., SVM, Decision Trees, ANNs) and model evaluation metrics (e.g., F1-score, precision, recall).