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 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 2027 and 2029. 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. Our Spring Co-Op program runs from Jan - Aug, 2027. In order to be considered for this role, you must be available to work full time (40 hours per week), onsite, for the entire duration. If you are unable to work during the spring semester, please apply to our Summer Internship Program. As a Machine Learning Research Intern on Rivian's Autonomy team, you will advance neural scene reconstruction and world modeling that turn real-world driving data into high-fidelity, re-renderable 3D environments. This research directly strengthens how we develop, test, and validate the ML models behind the autonomous driving system in Rivian's vehicles — raising both the speed and the safety confidence with which we ship autonomy to customers. Responsibilities Research, prototype, and train 3D machine learning models for scene reconstruction, novel view synthesis, and neural rendering from multi-sensor driving data (camera, lidar, radar, and vehicle pose). Investigate and extend modern approaches such as neural radiance fields, 3D Gaussian splatting, feed-forward reconstruction, depth and geometry estimation, and generative/diffusion-based scene synthesis. Design quantitative and qualitative evaluation methodology for reconstruction and rendering quality, including photometric, geometric, and downstream task-driven metrics. Scale training and inference pipelines to large real-world datasets using distributed, multi-GPU infrastructure. Collaborate with perception, simulation, and infrastructure teams to integrate research prototypes into our internal research platform. Present results regularly to the team, contribute to internal technical documentation, and deliver a final presentation summarizing your research contribution. Qualifications Must be currently pursuing a PhD degree at an accredited university. Actively pursuing a degree or one closely related in computer science, electrical engineering, statistics, or a closely related quantitative field. Research background in one or more of the following: 3D scene reconstruction, neural rendering / novel view synthesis, depth or geometry estimation, 3D scene understanding, or generative modeling. Track record of first-author publications at top-tier machine learning or computer vision conferences and journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, SIGGRAPH, CoRL, RSS). Strong proficiency in Python and a modern deep learning framework (PyTorch preferred), with demonstrated ability to implement, train, and debug models independently. Solid foundation in the mathematics underlying 3D vision: multi-view geometry, camera models, coordinate transforms, and 3D representations (point clouds, meshes, voxels, implicit fields). Experience applying 3D reconstruction, neural rendering, or world modeling to autonomous driving, robotics, or other embodied domains. Experience with large-scale distributed training and multi-GPU/multi-node workflows. Familiarity with simulation, sensor simulation, or synthetic data generation for training and evaluating ML systems. Experience working with large multi-sensor datasets and the calibration, synchronization, and data-quality challenges they involve. Open-source contributions, released research code, or a strong public portfolio of 3D ML work. Pay Disclosure The salary range for this role is $33.00-51.00/HR for Palo Alto 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. 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). 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 and Technology 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. How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role. AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate. Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way. Please note that we are currently not accepting applications from third party application services.