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

Rivian Palo Alto, CA

Palo Alto, CA

Today

Full time Artificial Intelligence Autonomous Driving Data Pipeline

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Job Description

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

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