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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 building the next generation of autonomy through a Large Driving Model (LDM) powering the Rivian Autonomy stack. As a Staff Machine Learning Engineer, you will lead the end-to-end lifecycle of the LDM, from data curation and post-training pipelines to evaluation and on-road production performance. This role combines deep model expertise with real-world autonomy impact, with technical leadership across the team and the autonomy roadmap.

What you’ll work on

Spearhead development of advanced driving capabilities by owning the full LDM lifecycle, including targeted data curation, post-training alignment, and rigorous evaluation pipelines.
Assess and improve model design across supervision quality, validation strategies, and scalable architectures that close the gap between offline LDM training and on-road performance.
Serve as a technical authority within the Autonomy department, providing definitive guidance on technology decisions, model architectures, and data strategies.
Guide tradeoffs with a strong understanding of business, safety, and operational implications, aligning decisions to company timelines and product needs.
Enable other engineers by architecting scalable, extendable, and collaborative ML systems and codebases, and establishing best practices for the broader LDM team.
Influence technical roadmaps and build consensus across perception, planning, and platform teams, including during challenging technical discussions.
Deploy, supervise, and iteratively enhance models as they transition from development into customer vehicles, with a focus on verified real-world performance.

What you bring

M.S. or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field.
7+ years of industry experience building complex, production-grade ML systems, with experience operating at a Staff or Lead level.
Expert-level, hands-on experience with Python and PyTorch.
Large-scale distributed training frameworks experience is highly preferred.
Deep expertise in foundation models and post-training methods (including fine-tuning and alignment), plus experience applying approaches for perception, prediction, or planning in autonomous driving or robotics.
Proven ability to own ML data verticals, including data curation, synthetic data generation, and building robust evaluation frameworks for complex behavioral models.
Solid fundamentals in linear algebra, geometry, optimization, algorithms, and data structures.
Exceptional communication skills, with proven ability to set technical direction, guide execution, and build consensus in a fast-paced environment.
Motivation to move ambiguous, complex ideas from development and validation through to a verified, shipping product.
Hands-on mindset: proactively identify systemic gaps, write critical-path code, and address technical voids as needed.
Prior experience with Automotive Self-Driving stacks or similarly complex, safety-critical robotics systems.

Location: Palo Alto, CA (onsite)

Technologies: Python, PyTorch

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