Applied Machine Learning Engineer, Integrated Mobility Infrastructure System

Develop and operate machine learning models to predict road user behavior and enable physical access control for Woven City. Collaborate with cross-functional teams to improve traffic safety and efficiency using time-series data and state estimation techniques.

• Design, develop, and operate predictive models for forecasting behavior of vehicles, pedestrians, and cyclists using time-series location data.
• Design, develop, and operate a physical access control system for people, vehicles, and goods in Woven City.
• Collaborate with engineers to define requirements, design architecture, code, and test.
• Collaborate with diverse teams including city platform, operations, security, and Toyota group companies.
• Mentor team members to enhance technical skills.

• Bachelor's degree in Machine Learning, Data Science, Statistics, Computer Science, or related field (Master's or PhD preferred) or equivalent experience.
• 3+ years of commercial system development experience with Python, PyTorch, TensorFlow, scikit-learn.
• Practical experience in machine learning software design, implementation, and operation.
• Knowledge of Git, Docker, CI/CD, and MLOps workflows.
• Good communication and problem-solving skills; business level proficiency in Japanese or English.