UIUC Research Park Intern - Machine Learning Compiler

About Rivian

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.

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.

We are seeking an intern for the ML Compiler team working on software tools to enable inference of deep learning networks hardware on Rivian Hardware Platforms. You will work closely with the Rivian Autonomy and Hardware teams and evaluate various implementation targeting for performance. You will help bring up new hardware and add support in the compiler for these hardware features.

• Work on the ML Compiler for mapping Autonomy ML models to Rivian Autonomy Processor (RAP1).
• Implement graph lowering passes in the compiler to enable compiling various models to RAP
  1.
• Implement hardware‑aware optimizations, memory‑efficient representations, and operator fusion, targeted to RAP
  1.
• Benchmark and analyze system performance across platforms and iterate to achieve optimal deployment efficiency.
• Verify functionality through functional simulation or emulation.

• Must be currently pursuing a bachelor’s, master’s, or PhD degree at the University of Illinois Urbana Champaign.
• Actively pursuing a degree or one closely related in Engineering.
• Good understanding of algorithms for Computer Vision applications, Deep Learning, Natural Language Processing, Artificial Intelligence or related fields.
• Experience with ML compilation stacks.
• Strong mathematical background and capability to analyze results.
• Good understanding of software fundamentals.
• Excellent C++ and Python programming skills.
• Must be enrolled in the University of Illinois Urbana Champaign.
• Must be able to work out of our office in the Research Park.
• Must be available for 20 hours per week in the Fall and Spring and 40 hours in the summer.
• This project will require weekly task status updates and monthly project updates.

The salary range for this role is $ per hour for Illinois based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.

We offer a comprehensive package of benefits including but not limited to paid vacation, paid sick leave, and medical insurance benefits. Internship positions are not eligible for retirement benefits. More information about benefits is available at

You can apply for this role through  (or through inte if you are a current employee). This job is not expected to be closed any sooner than 7/31/2026.

Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All…