Staff Machine Learning Engineer, End-to-End Autonomy

About Rivian Rivianis 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 We are seeking a Staff Machine Learning Engineer interested in the development of end-to-end models that unify perception, prediction, and planning in a single learning system. This role is ideal for someone excited by the challenge of scaling models that learn from vast sensory data to enable autonomous driving. Responsibilities As a member of the Autonomy team, you will guide the architecture, implementation, and deployment of the Large Driving Model (LDM). This model will support not only perception tasks (e.g., object detection, onboard map detection, scene understanding) but also downstream decision-making and closed-loop autonomy. Key areas of responsibility include: Developing technical strategy and architecture for end-to-end autonomous driving model Developing multi-modal, multi-task transformer-based systems that support closed-loop autonomy Building training and evaluation pipelines at scale across petabytes of real-world and simulated driving data Collaborating with cross-functional teams across perception, planning, simulation, and ML infrastructure Driving alignment between model capabilities and real-world deployment constraints (latency, robustness, validation) Publishing internal technical guidance and mentoring engineers across autonomy ML Qualifications B.S., M.S., or Ph.D. in Computer Science, Robotics, or a related field 5+ years of experience building and deploying large-scale ML systems Deep understanding of foundation models, self-supervised learning, and world models in robotics or simulation Strong software engineering background, with fluency in Python and C++ Experience training and evaluating transformer models or end-to-end autonomous agents Familiarity with real-time inference systems and autonomous vehicle constraints Proven leadership in driving ML projects from research to production Bonus Prior work on end-to-end autonomous driving architectures (e.g., imitation learning, behavior cloning, world models) Experience with sensor fusion (LiDAR, camera, radar) in a learned model 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. 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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. 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