Senior Machine Learning Engineer, Behavior Planning

Woven by Toyota is enabling Toyota's once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what "mobility" means and how it serves society.

Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we're working toward one bold goal: a world with zero accidents and enhanced well-being for all.

TEAM
The Behavior team at Woven by Toyota tackles autonomy challenges in prediction and trajectory planning. Our work involves a variety of technical hurdles, such as analyzing petabytes of multimodal driving data, solving optimization problems, minimizing latency on hardware accelerators, deploying scalable and efficient machine learning (ML) training and evaluation pipelines, and designing novel neural network architectures to advance state-of-the-art ML for prediction and motion planning. We are looking for driven and creative problem-solvers to join us in improving mobility for everyone through human-centered automated driving solutions for personal and commercial applications.

WHO ARE WE LOOKING FOR?
We are seeking a skilled Machine Learning Engineer to help advance cutting-edge ML systems for prediction and motion planning in autonomous driving. You will have the opportunity to design and implement innovative machine learning models for our next-generation autonomous vehicle platform, influencing millions of Toyota production vehicles. We are looking for individuals who are passionate about self-driving car technology and its transformative potential for humanity.

Responsibilities

• Design and develop advanced machine learning models in the behavior space, specifically tailored for autonomous vehicles, utilizing deep learning and large-scale data analysis.
• Deploy scalable and efficient ML models on our autonomous vehicle platform.
• Integrate modern technologies with rigorous safety standards while maintaining cost efficiency.
• Oversee the development of new ML models end-to-end, from data strategy and initial development to optimization, production platform validation, and fine-tuning based on metrics and on-road performance.
• Lead large, multi-person projects and significantly influence the overall motion planning architecture and technical direction.
• Enable and support other engineers by coaching, leading by example, and providing high-quality code and design document reviews, as well as delivering rigorous reports from ML experiments.
• Contribute significantly to the development of essential components for end-to-end ML training and deployment, from data strategy to optimization and validation.
• Be a champion of the scientific method and critical thinking to invent state-of-the-art deep learning solutions.
• Work in a high-velocity environment and employ agile development practices.
• Collaborate closely with teams such as Perception, Simulation, Infrastructure, and Tooling to drive unified solutions.

Qualifications

• MS or PhD in Machine Learning, Computer Science, Robotics, or related quantitative fields, or equivalent industry experience.
• 3+ years of experience with Python, PyTorch, distributed training and clean software engineering best practices (testing, code review, CI/CD).
• Comfortable writing C++ code for integration with our autonomous vehicle platform.
• 3+ years applying deep learning to sequential decision-making and prediction, including supervised/unsupervised/self-supervised learning, transfer/multi-task learning, and deep reinforcement learning.
• Extensive experience with modern sequential modeling on multi-modal sensor data (e.g., modern encoders, transformers, diffusion/latent-variable models, flow matching) and probabilistic modeling.
• 3+ years across end-to-end ML workflows: large-scale data sampling and curation, preprocessing, distributed training, ablation studies, robust evaluation, deployment, and inference optimization both for accelerators in inference time and also during training.
• Experience with learning-based decision-making for autonomous vehicles and how learned components interface between perception, motion planning and control.
• Passion for self-driving car technology and its potential to impact humanity.
• Strong communication skills with the ability to articulate concepts clearly and precisely.

NICE TO HAVES

• Published research at top-tier ML/robotics venues (e.g., NeurIPS, ICML, ICLR, CVPR, CoRL, RSS, IROS, ICRA).
• Proven track record of training and deploying large-scale multi-modal models for autonomy (e.g., behavior prediction, world models, diffusion/transformer policies) with distributed training and rigorous evaluation.
• Experience with data-centric ML: dataset design/curation at scale, active learning, auto/weak labeling, and synthetic data generation.
• Experience optimizing real-time on-vehicle inference (quantization/pruning/compilation; e.g., TensorRT, ONNX Runtime) and GPU profiling, with familiarity in production-level coding under time-limited schedules.
• Expertise across self-driving challenges (Perception, Prediction, Planning, Simulation) with emphasis on learned systems and robot motion planning.

What We Offer
We are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility.

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Excellent health, wellness, dental and vision coverage

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A rewarding pension

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Flexible vacation policy

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Family planning and care benefits

Our Commitment
・We are an equal opportunity employer and value diversity.

・Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.