Hybrid Backend, Applied Machine Learning Engineer, Integrated Mobility Infrastructure System

at Woven Planet

• Job title: Backend, Applied Machine Learning Engineer, Integrated Mobility Infrastructure System
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Docker, Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Tokyo, Japan

About the role

• Engineer developing and operating machine learning models for traffic safety at Woven by Toyota. Collaborating with diverse teams to improve traffic flow and enhance mobility solutions.

Responsibilities

• Design, develop, and operate predictive models to forecast the future behavior of various road users — including vehicles, pedestrians, and cyclists — based on time-series location and other relevant data
• Design, develop, and operate a physical access control system for people, vehicles, and goods to enable demonstration testing in Woven City
• Collaborate with other engineers to define requirements, design software architecture, engage in coding, and conduct testing
• Collaborate with diverse teams, including city platform, operations, security and other to ensure safe and comprehensive implementation of requirements
• Collaborate with stakeholders and partners, including TMC and other Toyota group companies
• Enhance the technical skills of team members through proactive contributions and mentorship

Requirements

• Bachelor degree in Machine Learning, Data Science, Statistics, Computer Science, or a related field (Master’s or Ph.D. preferred), or equivalent professional experience
• 3+ years of commercial or equivalent system development experience using programming languages such as Python, and frameworks such as PyTorch, TensorFlow, and scikit-learn
• Practical experience in technical selection, requirements analysis, design, implementation, operation, and continuous improvement of software in the field of machine learning
• Understanding of fundamental software development tools and processes, including Git, Docker, and CI/CD
• Knowledge of MLOps workflows, including data preparation, preprocessing, model training, evaluation, optimization, and deployment
• Good communication, a proactive mindset, and strong problem-identification and solving skills
• Business level proficiency in Japanese and passion to develop English skill.

Benefits

• Competitive Salary - Based on experience
• Work Hours - Flexible working time
• Paid Holiday - 20 days per year (prorated)
• Sick Leave - 6 days per year (prorated)
• Holiday - Sat & Sun, Japanese National Holidays, and other days defined by our company
• Japanese Social Insurance - Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance
• Housing Allowance
• Retirement Benefits
• Rental Cars Support
• In-house Training Program (software study/language study)