Engineering Manager for Machine Learning in Behavior Planning & Prediction

Woven by ToyotaPalo Alto, CA

On-site Full-time

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Experience Level

Manager

Qualifications

Proven experience as an Engineering Manager in machine learning or related fields. Strong background in developing and deploying machine learning models, particularly in autonomous systems. Expertise in data processing and creating efficient ML training pipelines. Hands-on experience with neural network architectures and optimization techniques. Passion for self-driving technology and its societal implications. Ability to thrive in a fast-paced, innovative environment. Excellent leadership and team management skills.

About the job

Our initiatives are built upon four foundational pillars: AD/ADAS, encompassing our autonomous driving and advanced driver assistance technologies; Arene, our software development platform tailored for software-defined vehicles; Woven City, a pioneering testbed for mobility innovations; and Cloud & AI, the digital backbone that supports our collaborative framework. Our business-critical functions empower these teams to collaborate effectively in pursuit of a singular, ambitious goal: to create a world devoid of accidents and enhance the well-being of all.

Team Overview

The Behavior team at Woven by Toyota addresses autonomous challenges related to prediction and trajectory planning. Our work encompasses an array of tasks, including the analysis of petabytes of multimodal driving data, optimization problem-solving, latency reduction on hardware accelerators, deployment of scalable and efficient machine learning (ML) training and evaluation pathways, and the design of innovative neural network architectures to push the boundaries of ML in Prediction and Motion Planning.

Candidate Profile

We are searching for a highly experienced, technically adept Engineering Manager to spearhead a team of talented engineers within the behavior group. This role emphasizes the development and implementation of cutting-edge machine learning models for planning and prediction in AD/ADAS, alongside their related data processing frameworks and vehicle integration. The ideal candidate should possess a profound enthusiasm for self-driving technology and its transformative potential on a global scale. You will guide your team in enhancing our core behavior machine learning models and associated pipelines. We seek an individual with deep expertise in machine learning, a thorough comprehension of the model lifecycle, and substantial experience in creating tools and pipelines to address behavioral challenges. Success in this role necessitates a candidate who flourishes in a dynamic environment, is hands-on, and is driven to expand the frontiers of our technology. Prior experience in developing and deploying real-world autonomous driving products and collaborating with exceptionally skilled engineers is crucial.

About Woven by Toyota

Woven by Toyota is pioneering the shift towards a mobility-centric future, emphasizing innovation that serves societal needs. Our focus on technology and collaboration aims to redefine how mobility is perceived and experienced, ultimately fostering a safer and more efficient world.

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Engineering Manager for Machine Learning in Behavior Planning & Prediction

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Full-time|On-site|Palo Alto, CA

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Feb 27, 2026

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Full-time|On-site|Palo Alto, CA

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Principal Machine Learning Engineer - Training Systems

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Full-time|On-site|Palo Alto

At Rhoda AI, we are pioneering the development of a comprehensive foundation for the next generation of humanoid robots. Our focus spans high-performance, software-defined hardware to advanced foundational models and video world models that govern robot functionality. Our robots are engineered to be versatile, capable of navigating intricate, real-world environments and tackling scenarios not previously encountered in training. We stand at the crossroads of large-scale learning, robotics, and systems, bolstered by a research team comprising experts from prestigious institutions such as Stanford, Berkeley, and Harvard. Our ambition is not merely to add features; we are crafting a revolutionary computing platform for physical tasks, underpinned by over $400 million in funding, driving aggressive investments in research & development, hardware innovation, and scaling up manufacturing to bring our vision to fruition.Role OverviewWe are in search of a Principal Machine Learning Systems Engineer to take charge of our training systems' performance from start to finish. You will be instrumental in defining the scaling of our model training, enhancing efficiency, scalability, and accuracy across extensive multimodal training environments. This is a pivotal systems role, not merely focused on infrastructure support. Your contributions will significantly influence our compute utilization efficiency, scalability of models across thousands of GPUs, and the speed of research iterations.Your ResponsibilitiesOversee training performance from start to finishAnalyze and enhance the performance of large-scale multimodal training encompassing vision, video, proprioception, actions, and language.Create systematic performance attributions by breaking down step-time into compute, communication, and input pipeline, along with scaling curves for various cluster sizes and identifying key bottlenecks.Drive quantifiable improvements across:Distributed efficiency (e.g., communication and compute overlap, bucketization, topology-aware mapping, and parallelism strategies).Compute efficiency (e.g., identifying kernel hotspots, operator fusion, attention optimization, and minimizing framework/runtime overhead).Memory efficiency (e.g., activation checkpointing, sequence packing, and reducing fragmentation).Design training systems rather than just tuning themDefine and refine parallelism strategies including data, tensor, pipeline, sharding, and hybrid approaches.Enhance execution efficiency through communication scheduling, graph capture, execution optimization, and runtime enhancements.Contribute to the overall system architecture with innovative solutions.

Mar 10, 2026

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Full-time|On-site|Palo Alto, CA

Role Overview:Join Nace.AI as a Machine Learning Engineer, where you will be instrumental in transforming advanced machine learning research into scalable, production-ready applications. Collaborating with interdisciplinary teams, you will pinpoint areas where machine learning can enhance product offerings, design robust model-centric architectures, and guarantee their smooth integration into practical applications. This role demands a harmonious blend of theoretical insight and hands-on engineering, focusing on creating dependable, maintainable, and impactful AI-driven features that align with Nace.AI's strategic goals.Key Responsibilities:Develop and sustain complete ML systems, including synthetic data pipelines, model training, debugging, and performance assessment.Enhance large language models (LLMs) and utilize meta-learning strategies to boost model generalization and efficiency.Refine existing Nace.AI models by integrating breakthroughs from the latest ML research.

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