Staff ML Platform Engineer - AD/ADAS

About Woven by Toyota Woven by Toyota contributes to Toyota's transformation into a mobility company once-in-a-century. Inspired by our history of continuing to invent "for someone other than ourselves," our mission is to expand the definition of mobility, extend the ways mobility contributes to society, and continue challenging the common sense of mobility through innovation that thinks of people.

We operate around four pillars: AD/ADAS (Automated Driving/Advanced Driver Assistance Systems) technology, Arene, a vehicle software production platform for SDV (Software Defined Vehicle); 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 toward the realization of a "zero accident society" and the "mass production of happiness."

=========================================================================

About the Team In the AD/ADAS team at Woven by Toyota, we tackle autonomous driving challenges at the intersection of AI, robotics, and advanced driving technology. We perform analysis of vast amounts of multimodal driving data, optimization of computer vision algorithms, minimization of latency using hardware acceleration, deployment of scalable and efficient machine learning and evaluation pipelines, and the design of innovative neural network architectures to advance cutting-edge machine learning in the fields of perception, prediction, and planning. We are looking for teammates with execution power and creative problem-solving abilities to improve mobility for all people through human-centric autonomous driving solutions for both personal and commercial use.

Who We Are Looking For In the ML Platform team, we are looking for an excellent software engineer or machine learning engineer who can work closely and cooperatively with machine learning teams to accelerate and expand the development of our ML technology. You will develop machine learning models for perception, prediction, and path planning, as well as AD/ADAS technology, and deploy them to millions of Toyota production vehicles.

We are looking for someone who is passionate about autonomous driving technology and its impact on humanity, utilizes cutting-edge technology, and can solve real-world problems while considering engineer productivity and cost efficiency. We also welcome those who always maintain a "giver" mindset and a spirit of helping teammates, with a strong awareness of providing solutions toward product development.

Responsibilities

• Design, build, maintain, optimize, and support machine learning platform systems and tools to enable many ML engineers to efficiently perform dataset curation, modeling, training, evaluation, implementation, etc., in autonomous driving perception, prediction, and path planning development.
• Develop easy-to-use tools, frameworks, and libraries—from modeling and performance metric monitoring to failure mode root cause analysis—to facilitate the entire ML engineering development process.
• Build and maintain efficient data curation and training/evaluation pipelines on the cloud.
• Conduct code development and reviews together with other ML engineers and platform engineers to promote improvement.
• Optimize current processes, tools, and infrastructure to facilitate the entire ML engineering development. Contribute to the formulation of long-term strategies.
• Development in an agile, fast-paced environment.
• Work 3 days a week at the Nihonbashi (Japan) office based on a hybrid work policy.
• Collaborate cross-functionally on the system's target architecture and optimize processes and systems globally.

Requirements

• Bachelor's degree in Machine Learning, Computer Science, Robotics, or a related field (Master's or PhD preferred), or equivalent practical experience.
• 10+ years of experience in data structures, algorithms, design patterns, and software engineering best practices.
• 4+ years of experience with UNIX-like systems (Linux, etc.), Python, and PyTorch or TensorFlow.
• 4+ years of experience across the entire MLOps cycle, including data cleansing, sampling, curation, preprocessing, training, testing, evaluation, deployment, inference optimization, and deployment on cloud and edge.
• Experience in scaling machine learning training in large-scale environments and solving typical challenges associated with it.
• Experience using CI systems such as Docker and GitHub Actions.
• Business-level English proficiency capable of creating software documentation.

Preferred Qualifications

• 4+ years of experience with machine learning pipelines (Apache Spark, Airflow, Flyte, Flink, Ray).
• 4+ years of experience with modern system programming languages such as Rust or C++, and build systems such as Bazel. Knowledge of system-level debugging.
• Extensive experience as a software architect or senior manager.
• Experience in SIMD/SIMT parallel processing, GPU programming, and multi-threaded processing.
• Experience using Terraform, AWS, Observability, Kubernetes, etc., in production environments.
• Experience operating analytical platforms such as Google Big Query, Snowflake, or AWS Redshift.
• Experience in optimizing deep learning models for specific hardware.
• Experience in autonomous driving, robotics, computer vision, or path planning.
• Experience developing cross-functionally in a fast-paced development environment.
• Business-level Japanese proficiency.

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

• Typically, all interviews are conducted via Google Meet.
• Job postings are currently listed in both English and Japanese. Therefore, 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 varies in the first year depending on the month of joining).
• Sick leave: 6 days per year (number of days varies in the first year 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 benefit system.
• Rental car support.
• Internal training programs (software learning, language learning).

Our Commitment

• We provide equal employment opportunities and respect diversity.
• Personal information provided will be used only for recruitment and onboarding procedures. For details, please refer to the Privacy Policy.