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

Rivian is seeking a Staff Machine Learning Engineer to contribute to the development and deployment of its next-generation Large Driving Model (LDM) within the Rivian Autonomy stack. This role spans the complete model lifecycle, from data curation and post-training to evaluation and real-world, on-road performance, with technical leadership across autonomy teams.

Responsibilities

• Lead the development of advanced driving capabilities by owning the full Large Driving Model (LDM) lifecycle, including targeted data curation, post-training alignment, and rigorous evaluation pipelines.
• Review and improve model design choices to ensure high-quality supervision, robust validation strategies, and scalable architectures that close the gap between offline LDM training and on-road performance.
• Serve as a technical authority in the Autonomy department, providing decisive guidance on technology choices, model architectures, and data strategies for current and future initiatives.
• Evaluate business, safety, and operational implications of technology tradeoffs, balancing them in line with company timelines and product needs.
• Build scalable, extendable, and collaborative ML systems and codebases to enable other engineers, and define best practices for the broader LDM team.
• Influence technical roadmaps and help drive consensus across perception, planning, and platform teams during complex technical discussions.
• Own model transition to production by deploying, supervising, and continuously improving real-world on-road performance as models move from development into customer vehicles.

Requirements

• M.S. or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field.
• 7+ years of industry experience delivering complex, production-grade Machine Learning systems, with experience operating at a Staff or Lead level.
• Expert-level 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 and post-training paradigms (fine-tuning, alignment), with experience across perception, prediction, or planning for autonomous driving or robotics.
• Proven ability to own full ML data verticals, including data curation, synthetic data generation, and building robust evaluation frameworks for complex behavioral models.
• Strong foundations in linear algebra, geometry, optimization, algorithms, and data structures.
• Exceptional communication skills, including the ability to set technical direction, guide execution, and build consensus in a fast-paced environment.
• Motivation to move ambiguous and complex ideas from development and validation to a verified, shipping product.
• Hands-on approach, including proactively identifying systemic gaps and writing critical path code when needed.
• Prior experience with Automotive Self-Driving stacks or similarly complex, safety-critical Robotics Systems.

Required Education

M.S. or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field.

Location

Palo Alto, CA (onsite)

Technology Stack

• Python
• PyTorch