Data Platform Software Engineer · Enterprise AI

About Woven by Toyota Woven by Toyota contributes to Toyota's transformation into a mobility company for the first time in 100 years. Inspired by our history of inventing "for someone other than ourselves," our mission is to expand the definition of mobility, extend the ways mobility contributes to society, and continue to challenge the common sense of mobility through innovation that thinks of people.

We operate around four main pillars: AD/ADAS (Automated Driving/Advanced Driver Assistance Systems) technology, Arene—a vehicle software production platform for SDV (Software Defined Vehicles), Woven City—a mobility test course, and Cloud & AI—the digital infrastructure that supports our collaborative foundation. Additionally, essential business functions support the implementation of these teams, working together as one to realize a "zero accident society" and the "mass production of happiness."

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About the Team The Enterprise AI team is dedicated to providing a powerful AI innovation platform to Toyota and its affiliates. Our mission is to provide a comprehensive end-to-end machine learning ecosystem to drive groundbreaking projects such as automated driving within the Toyota Group. As the standardized machine learning platform for "Woven by Toyota," we aim to streamline every aspect of AI development—from training and inference to MLOps (Machine Learning Operations)—to improve the safety, convenience, and autonomy of Toyota vehicles.

Within this dynamic environment, the Data Platform Engineering team plays a critical role. We design and implement scalable, globally distributed data delivery solutions tailored to Toyota and its partners. Our team is at the forefront of development for both human-assisted and automated data labeling services, engaging collaboratively through various model development and AI solution initiatives. Through these efforts, we ensure that data is not only accessible but also actionable, fostering innovation and efficiency across the enterprise.

Requirements As a Backend Engineer, you will support the development of labeling capabilities while collaborating with Machine Learning Engineers distributed across different regions. You will provide large-scale datasets to users spanning multiple countries. Our goal is to transform the acquisition and delivery of data labeled by humans and machines, accelerating the global advancement of machine learning projects.

You must possess both technical and communication skills. As a member of the team, we respect healthy, constructive, and positive feedback to improve our development quality together. We promote refactoring, rewriting legacy code, profiling, code style, and code reviews.

Responsibilities

• Execute everything from feature design to deployment.
• Solve complex problems and provide cutting-edge solutions.
• Collaborate with Team Leads and Software Engineers to develop the backend for labeling feature sets, ensuring product functional and non-functional requirements are met.
• Support multiple machine learning training data formats and enable real-time conversion.
• Integrate with multiple data sinks, such as machine learning data visualization solutions, using datasets owned by the Data Annotation Engineering team.
• Work closely with Frontend Developers to establish and maintain API contracts.
• Report directly to the Manager in charge of the Data Annotation Engineering team.

Minimum Qualifications

• At least 4 years of experience in Python development, with at least 2 years dedicated to asynchronous Python programming, and a fundamental understanding of machine learning.
• Proficiency in handling large-scale datasets. This includes databases with massive rows or documents, and a solid understanding of concurrency, distributed computing, and Blob storage.
• Familiarity with event-driven architecture utilizing multiple message queues (channels).
• Knowledge of major RDBMS and NoSQL databases such as PostgreSQL and MongoDB.
• Hands-on experience with Kubernetes.
• Ability to work in the office 3 days a week in accordance with the hybrid work model.
• Business-level English proficiency.

Preferred Qualifications

• Ability to contribute to open-source projects and analyze open-source software.
• Knowledge of spatial/geometric information or vector databases.
• Experience with PyTorch data loaders or 2D/3D-based machine learning training data formats.
• Understanding of machine learning, particularly deep learning.
• Knowledge of image and point cloud processing technologies.
• Proficiency in one or more programming languages commonly used in machine learning or large-scale parallel computing environments.

========================================================================= Notes

• Typically, all interviews are conducted via Google Meet.
• Job postings are currently listed in both English and Japanese. Please apply to only one of them.
• When applying, we request that you submit an English resume if possible. Please note that if you submit a Japanese resume for any reason, we may request an English resume during the selection process depending on the position.

Compensation and Benefits

• Salary commensurate with industry standards based on experience.
• Working Hours: Flexible working hours.
• Annual Paid Leave: 20 days per year (number of days in the first year varies depending on the month of joining).
• Sick Leave: 6 days per year (number of days in the first year varies depending on the month of joining).
• Holidays: Saturdays, Sundays, national holidays, and other days designated by the company.
• Social Insurance: Health insurance, Employees' Pension Insurance, Industrial Accident Compensation Insurance, Employment Insurance, Nursing Care Insurance.
• Housing Allowance.
• Retirement Allowance System.
• Rental Car Support.
• Internal Training Programs (Software learning, Language learning).

Our Commitment

• We provide equal employment opportunities and respect diversity.
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