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. Role Summary 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. Responsibilities 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. Qualifications 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). C/C++ Proficiency: Practical experience with C or C++ for embedded systems development and code review. Signal Processing Foundation: Demonstrated coursework or project experience with techniques like FFT, Wavelet Transforms, or Control Theory, preffered. Understanding of Functional Safety (ISO 26262) principles, preffered. #LI-HH2 Pay Disclosure The salary range for this role is $25.00-40.00 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 rivianbenefits.com. You can apply for this role through careers.rivian.com (or through internal-careers-rivian.icims.com if you are a current employee). This job is not expected to be closed any sooner than 7/31/2026. Equal Opportunity Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law. Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com. Candidate Data Privacy Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (“Candidate Personal Data”). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law. Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services. Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions. Please note that we are currently not accepting applications from third party application services.
Uiuc Research Park Intern - ML AI Motor Controls Algorithm
This internship role focuses on developing an integrated analytical workflow for motor controls algorithms using cloud infrastructure, LLMs, and traditional ML. The intern will be responsible for data and feature engineering, signal processing, ML model building, system integration, and data visualization to derive insights from vehicle data.
What you'd actually do
- Design and implement robust Python-based tools to parse, decode, and extract features from automotive PCAP logs.
- Apply advanced signal-processing techniques to transform vehicle data and perform large-scale analysis of corner cases of interest.
- Research, develop, and train machine learning models (e.g., Decision Trees, Random Forests, Neural Networks) for prediction, detection, and classification tasks.
- Architect the end-to-end workflow that processes raw vehicle logs, performs automated analysis, and prepares data for model training.
- Create easy-to-understand dashboards for the general audience, focusing clearly on outcomes to support decision making.
Skills
Required
- Masters or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or Physics
- Proficiency in AI practices and feeding LLM with data and knowledge base
- Expertise in Python (including Pandas, NumPy, Scikit-learn)
- Deep theoretical and practical understanding of classification algorithms (e.g., SVM, Decision Trees, ANNs) and model evaluation metrics (e.g., F1-score, precision, recall).
- Practical experience with C or C++ for embedded systems development and code review.
Nice to have
- Signal Processing Foundation: Demonstrated coursework or project experience with techniques like FFT, Wavelet Transforms, or Control Theory
- Understanding of Functional Safety (ISO 26262) principles
What the JD emphasized
- Proficiency in AI practices and feeding LLM with data and knowledge base
Other signals
- develop an integrated analytical workflow
- leverages Cloud infrastructure and Large Language Models (LLMs), alongside traditional machine learning
- derive actionable insights from complex vehicle data
- architecting an automated, cloud-connected system for high-level data preparation and analysis
- Data & Feature Engineering
- Signal Processing
- ML Model Building
- System Integration
- Data visualization