Rivian had H-1B petitions approved for 493 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. See the record
At a glance
Staff Machine Learning Engineer- Large Driving Model (LDM), Motion Planning, Autonomy at Rivian, an on-site role based in Palo Alto, California, USA. Experience level: 7+ Years. Pay stated in the posting: $209,800.00 to $285,000.00. Posted on 20 October 2026, read from Rivian's own careers page (Jibe), which RealAnalystJobs re-checks daily and removes the role when it closes. Rivian has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role).
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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 We are seeking a Staff Machine Learning Engineer to play a foundational role in building and deploying our next-generation Large Driving Model (LDM) for the Rivian Autonomy stack. To solve this, we are leveraging massive-scale Machine Learning powered by millions of miles of driving data. In this highly impactful role, you will own a full vertical of the LDM lifecycle, from large-scale data curation and post-training pipelines through to rigorous evaluation to implement and perfect specific, advanced driving capabilities. As a Staff Engineer, you will lead the AI strategy for these capabilities, serving as a primary technical authority. Your work will directly translate to the daily experience, comfort, and safety of our customers, which is critical to the core mission at Rivian. If you are passionate about pushing the boundaries of generative and foundation models in the physical world, shipping cutting-edge improvements to customers, and driving technical consensus across a high-performing team, we want to talk to you. Responsibilities End-to-End Vertical Ownership: Spearhead the development of specific advanced driving capabilities by owning the full lifecycle within the Large Driving Model (LDM), including targeted data curation, post-training alignment, and rigorous evaluation pipelines. Model & System Design: Examine and optimize all aspects of successful model design, ensuring high-quality supervision, robust validation strategies, and scalable architectures capable of bridging the gap between offline LDM training and on-road performance. Technical Leadership: Act as a recognized technical authority within the Autonomy department, offering definitive guidance on current and future technology decisions, model architectures, and data strategies. Strategic Tradeoffs: Possess an in-depth grasp of the business, safety, and operational implications of various technology tradeoffs, effectively balancing them according to the company's timeline and product needs. Engineering Excellence: Empower fellow engineers by architecting scalable, easily extendable, and collaborative ML systems and codebases. Establish best practices for the broader LDM team. Cross-Functional Alignment: Display the ability to influence technical roadmaps and foster consensus across perception, planning, and platform teams, even during challenging technical discussions. Production Focus: Take charge of deploying, supervising, and enhancing the real-world, on-road performance of your models as they transition from the development phase into customer vehicles. Qualifications M.S. or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field. 7+ years of industry experience working on complex, production-grade Machine Learning systems, with a track record of operating at a Staff or Lead level. Expert-level knowledge and hands-on experience with Python and PyTorch. Experience with large-scale distributed training frameworks is highly preferred. Deep expertise in state-of-the-art foundation models, post-training paradigms (fine-tuning, alignment), and approaches for perception, prediction, or planning in the autonomous driving or robotics space. Proven ability to own full ML data verticals, demonstrating mastery over data curation, synthetic data generation, and building robust evaluation frameworks for complex behavioral models. Solid foundational understanding of linear algebra, geometry, optimization, algorithms, and data structures. Exceptional communication skills with a demonstrated ability to set technical direction, guide the team toward it, and build consensus in a fast-paced environment. Passionately motivated to take ambiguous, complex ideas from development and validation all the way to a verified, shipping product. Hands-on approach: Proactively identifies systemic gaps, writes critical path code, and fills in technical voids where needed. Prior experience with Automotive Self-Driving stacks or similarly complex, safety-critical Robotics Systems. Pay Disclosure The salary range for this role is $209,800.00 - $285,000.00 for California 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. The successful candidate may be eligible for annual performance bonus and equity awards. We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian’s 401(k) Plan and Employee Stock Purchase Program if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com. You can apply for this role through careers.rivian.com (or through internal-careers-rivian.i
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