Backend / Applied Machine Learning Engineer, Integrated Mobility Infrastructure System

About Woven by Toyota
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.

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TEAM
Toyota is redefining what it means to move. We're challenging the current state of mobility by enhancing the movement of people, goods, information and energy. Centered around three core concepts - A Living Laboratory™, Human-Centered, and Ever Evolving City™ - Woven City serves as a test course for mobility to fulfill our purpose of well-being for all.

We do this by bringing together a diverse community of people with a shared passion for the future of mobility to co-create, develop and refine innovative products and services. This cross-section of social infrastructure, mobility, and people provides a unique opportunity for inventors, residents and visitors to interact seamlessly with new technologies throughout daily life in an environment that emulates a real city.

For more information about Woven City, please visit: https://www.woven-city.global/

WHO ARE WE LOOKING FOR?
We are committed to achieving zero traffic fatalities and injuries by advancing traffic safety through the integrated efforts of people, mobility, and infrastructure. Focusing particularly on the infrastructure domain, we are dedicated to developing products that achieve both smooth traffic flow and enhanced safety. To accelerate these efforts, we are seeking highly motivated and passionate engineers with strong technical expertise, who understand machine learning model architectures and have experience applying them in production environments, as well as improving their performance. In this role, you will leverage your knowledge from the transportation and mobility fields—or other relevant domains—to develop and operate machine learning models. Your work will directly contribute to delivering services that improve traffic safety and optimize traffic efficiency.

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

MINIMUM QUALIFICATIONS:
• 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

NICE TO HAVES:
• Experience in developing algorithms for position estimation or collision prediction using time-series location data and map information
• Experience in data analysis and modeling of time-series data
• Experience in data analysis and modeling of map information and GIS (Geographic Information System) datasets
• Understanding and practical application experience with probabilistic generative models and state estimation models
• Industry knowledge in fields such as transportation and autonomous driving
• Business level proficiency in English

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Important Points
・All interviews will be arranged via Google Meet, unless otherwise stated.
・The same job descriptions are available in both English and Japanese; therefore, we kindly ask that you apply to only one version.
・We kindly request that you submit your resume in English, if possible. However, Japanese resumes are also acceptable. Please note that, depending on the English proficiency requirements of the role, we may request an English version of your resume later in the process.

WHAT WE OFFER
・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)

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.