Staff Machine Learning Engineer- Large Driving Model (LDM), Motion Planning, Autonomy

Rivian•Palo Alto, CA

About The Position

Rivian is seeking a Staff Machine Learning Engineer to play a foundational role in building and deploying its next-generation Large Driving Model (LDM) for the Rivian Autonomy stack, using machine learning powered by millions of miles of driving data. The engineer will own a full vertical of the LDM lifecycle, from large-scale data curation and post-training pipelines through rigorous evaluation, to implement and refine advanced driving capabilities. The role leads AI strategy for assigned capabilities and serves as a primary technical authority. Its work will directly affect customers’ daily experience, comfort, and safety. The successful candidate will take advanced driving capabilities from development through deployment and on-road monitoring in customer vehicles. They will guide technology and architecture decisions, balance business, safety, and operational tradeoffs, establish engineering practices, and build consensus across autonomy teams. The role is intended for someone who can take complex, ambiguous ideas through validation and into a verified, shipping product.

Requirements

M.S. or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field.
At least 7 years of industry experience working on complex, production-grade machine learning systems, with a track record at Staff or Lead level.
Expert-level knowledge and hands-on experience with Python and PyTorch.
Deep expertise in foundation models, post-training paradigms such as fine-tuning and alignment, and approaches to perception, prediction, or planning in autonomous driving or robotics.
Demonstrated ownership of full ML data verticals, including data curation, synthetic data generation, and robust evaluation frameworks for complex behavioral models.
Foundational understanding of linear algebra, geometry, optimization, algorithms, and data structures.
Exceptional communication skills and demonstrated ability to set technical direction, guide a team, and build consensus in a fast-paced environment.
Motivation and ability to take ambiguous, complex ideas from development and validation through to a verified, shipping product.
Hands-on approach, including proactively identifying systemic gaps, writing critical-path code, and filling technical voids.
Prior experience with automotive self-driving stacks or similarly complex, safety-critical robotics systems.

Nice To Haves

Experience with large-scale distributed training frameworks.

Responsibilities

Own the end-to-end lifecycle of specific advanced driving capabilities within the Large Driving Model, including targeted data curation, post-training alignment, and evaluation pipelines.
Design and optimize models and systems, including supervision quality, validation strategies, and scalable architectures that connect offline LDM training with on-road performance.
Provide technical direction and guidance on technology decisions, model architectures, and data strategies within the Autonomy department.
Balance technology tradeoffs according to business, safety, operational, timeline, and product considerations.
Architect scalable, extensible, collaborative ML systems and codebases; establish best practices for the LDM team.
Influence technical roadmaps and build consensus across perception, planning, and platform teams.
Deploy, supervise, and improve models’ real-world on-road performance as they transition into customer vehicles.
Identify systemic gaps, write critical-path code, and address technical needs hands-on.

Benefits

Paid vacation
Paid sick leave
Life insurance
Medical insurance
Dental insurance
Vision insurance
Short-term disability insurance
Long-term disability insurance
401(k) Plan, subject to eligibility requirements
Employee Stock Purchase Program, subject to eligibility requirements
Annual performance bonus and equity awards may be available to the successful candidate