Senior Machine Learning Engineer, Behavior Planning & Prediction

Senior Machine Learning Engineer, Behavior Planning & Prediction

Woven by Toyota is enabling Toyota’s transformation into a mobility company. 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, Arene, Woven City, and Cloud & AI. Business-critical functions empower these teams to execute, with the goal: a world with zero accidents and enhanced well-being for all.

The Behavior team tackles autonomy challenges in prediction and trajectory planning, including analysis of multimodal driving data, optimization, latency reduction on hardware accelerators, scalable ML pipelines, and novel neural architectures to advance state-of-the-art ML for prediction and motion planning. We seek driven problem-solvers to improve mobility through human-centered automated driving solutions for personal and commercial applications.

• 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.

• 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., 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 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.

• 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 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.

• We are committed to creating a modern work environment that supports our employees and their loved ones. We offer programs to enable you to do your most meaningful work and shape the future of mobility.
• Excellent health, wellness, dental, and vision coverage
• A rewarding pension
• Flexible vacation policy
• Family planning and care benefits

• 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.

Mid-Senior level

Full-time

Engineering and Information Technology

Software Development