UIUC Research Park Intern - Machine Learning Hardware

Rivian•Champaign, IL

17d•$25 - $40

About The Position

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations. Role Summary Internship Term: Summer 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. This role would focus on supporting power and performance tradeoff analysis on hardware for machine learning models.

Requirements

Must be currently pursuing a bachelors, masters, or PhD degree at the University of Illinois Urbana Champaign.
Actively pursuing a degree or one closely related in Computer Engineering or Computer Science.
Solid programming skills in C/C++ and Python. Willingness to dig into low level software programming if need be.
Good understanding of algorithms for Computer Vision applications, Deep Learning, Natural Language Processing, Artificial Intelligence or related fields
Strong mathematical background and capability to analyze results
Good understanding of software fundamentals
Understanding of core deep learning principles (e.g., transformer architecture basics)
Working knowledge of PyTorch for fine tuning and evaluating ML models.
Must be available for 20 hours per week in the Fall and Spring and 40 hours in the summer.
#LI-HH2

Responsibilities

Work on software tools for machine learning compiler to enable interence of deep learning networks on Rivian Hardware.
Work closely with software engineers to bringup up new models using compiler constraints on Rivian hardware.
Analyze compiler generated solutions and evaluate for performance and memory usage.
Verify functionality through functional simulation or emulation.
Analyze tradeoffs on various performance metrics including accuracy, latency, and throughput