Machine Learning Engineer- Driving Model; LDM), Motion Planning, Autonomy

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.

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.

• 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.

• 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,…