Woven by Toyota is enabling Toyota's transformation into a mobility company by developing human-centric innovation in autonomous driving, software-defined vehicles, and smart city infrastructure. The Behavior team is focused on tackling autonomy challenges in prediction and trajectory planning for personal and commercial applications, aiming to improve mobility and reduce accidents.
Requirements
- 3+ years of experience with Python, major deep learning frameworks, and software engineering best practices.
- Built robust data pipelines, ETL workflows, and integration systems to support behavior prediction models
- Expertise with deep learning approaches, such as supervised/unsupervised learning, transfer learning, multi-task learning, and deep reinforcement learning.
- Good understanding of learning-based planning approaches, including imitation learning, reinforcement learning, and state-of-the-art techniques for sequential modeling, such as Transformer architectures.
- Practical experience with ML training and evaluation workflows, including data sampling, preprocessing, and reproducible experiment management.
- 3+ years of experience covering machine learning workflows, data sampling and curation, preprocessing, model training, ablation studies, evaluation, deployment, and inference optimization.
- Comfortable writing C++ code for integration with our autonomous vehicle platform.
Responsibilities
- Design, build, and maintain ML pipelines that produce training and evaluation data for behavior and prediction models, including ETL, feature extraction, augmentation, and labeling workflows.
- Implement auxiliary pipelines for model validation, metric computation, and on-road performance integration.
- 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.
- Contribute significantly to the development of essential components for end-to-end ML training and deployment, from data strategy to optimization and validation.
Other
- MS or PhD in Machine Learning, Computer Science, Robotics, or related quantitative fields, or equivalent industry experience.
- Passion for self-driving car technology and its potential to impact humanity.
- Strong communication skills with the ability to articulate concepts clearly and precisely.
- 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.
