Senior Machine Learning Software Engineer, Behavior ML Planning & Prediction
About Woven by Toyota Woven by Toyota will contribute to Toyota's transformation into a mobility company once in a hundred years. 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 to challenge the common sense of mobility through innovation that considers people.
We operate around four main pillars: AD/ADAS (Automated Driving and 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 as one to realize a "zero accident society" and the "mass production of happiness."
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About the Team The Behavior team at Woven by Toyota is building the data foundation that supports data-driven automated driving. Our work is diverse: analyzing petabyte-scale multimodal vehicle and simulation data, designing scalable data pipelines from data ingestion to visualization, and providing normalized datasets, metrics, and self-service tools that support ML-based Motion Planning both on-board and off-board. We are looking for teammates with execution power and creative problem-solving skills to improve mobility for everyone through human-centric automated driving solutions.
Requirements We are looking for an experienced Senior Data Engineer who will work closely with the ML and Platform teams to discover, transform, and provide high-quality datasets. You will build data pipelines from ingestion to visualization and provide tools and introspection so that other members can build upon our data with confidence. By designing and owning the data architecture behind multiple large-scale projects, integrating data products into a single source of truth, and accelerating the release of models for next-generation automated driving vehicle platforms, you can impact millions of Toyota's production vehicles. We are looking for someone passionate about automated driving technology and the possibilities it brings to humanity.
As a senior member, you will take on the role of a technical leader, contributing to engineer mentoring, setting data engineering quality standards, and improving the data capabilities of surrounding teams. We highly value a "Giver" mindset that constantly asks "What can I do for you?" and the conviction to persist in advocating for the right long-term design, even during difficult dialogues.
This position carries significant discretion and a wide scope of responsibility. You will define technical directions that have a long-lasting impact beyond individual projects, tackle ambiguous zero-base challenges where the correct structure has not yet been defined, and expand your scope of influence and technical leadership as the data platform matures. This is an ideal position for an outstanding senior engineer ready to excel from a broader perspective across the entire organization.
We welcome those who prefer hybrid working and can come to the Nihonbashi (Tokyo) office three days a week.
Responsibilities Own the end-to-end data architecture to integrate data across the entire organization and define its technical direction. Instead of local optimization, take a long-term perspective to consolidate the platform into a consistent, searchable, and reliable one while evaluating design and operational trade-offs regarding scalability, reliability, and cost.
Design and build data pipelines from data ingestion to transformation, delivery, and visualization. Convert raw vehicle and simulation logs into reliable, reusable, normalized datasets, extracting data value through discovery, modeling, and delivery while maintaining consistency across teams.
Define common technical directions across teams. Collaborate with stakeholders across the organization to understand their data needs, rigorously and objectively evaluate technical trade-offs, influence roadmaps, and lead consensus toward a single source of truth. In doing so, present critical insights clearly to both technical and non-technical audiences.
Define and own data products, Service Level Agreements (SLAs), and self-service dashboards or tools that scale analysis across the organization for your assigned datasets, and build the monitoring, alerting, and operational frameworks to uphold those promises.
Reduce risk through rapid prototyping and intensive technical research before the organization commits to major architectural decisions, turning unresolved questions into evidence-based decision-making.
Clearly document architecture, data models, interfaces, and decisions to ensure that designs, trade-offs, and the resulting datasets are easy for other members across the organization to understand, utilize, and maintain.
Act as a technical leader across teams. Mentor engineers, establish data engineering best practices and standards that are adopted by other teams, and enhance the data capabilities of the entire Autonomy organization.
Requirements 7+ years of experience building and operating large-scale production data pipelines and data platforms.
Deep proficiency in SQL and modern programming languages (e.g., Python), with practical experience designing robust data models and multi-step ETL/ELT jobs.
Experience using cloud data warehouses (e.g., BigQuery, Snowflake, Redshift) and orchestration/transformation tools (e.g., dbt, Airflow, etc.).
A track record of owning data architecture for large-scale systems and defining technical directions, with clear consideration of trade-offs between scalability, reliability, security, and cost.
A track record of cross-team technical leadership. Experience defining engineering standards adopted by other teams, building consensus with stakeholders who have different priorities or technical choices, driving organizational decision-making to completion without formal authority, and enhancing the capabilities of other engineers.
Ability to thrive in ambiguity. Ability to take on cross-functional challenges that are not clearly defined and create clarity, structure, and momentum to solve them.
Excellent English communication skills, with the ability to explain complex technical trade-offs clearly and persuasively.
Preferred Qualifications Experience integrating and aggregating data from multiple pipelines, formats, and storage systems into a common platform, or migrating from proprietary dataset formats to open table formats (e.g., Apache Iceberg) that serve as the foundation for lakehouse architecture.
Experience establishing data products, contracts, and SLAs for widely used datasets, as well as operating data quality frameworks and observability.
Experience handling and modeling large-scale, multimodal data (including spatial data and time-series/sequential data; e.g., sensors, logs, simulation, time-series data, trajectories, scene/snapshot representations) for reliable downstream use.
Understanding of concepts in the automated driving or robotics domain (e.g., vehicle motion — kinematics/dynamics, trajectories, coordinate systems; motion planning and prediction; perception; maps/localization) and how they shape the data they handle.
Knowledge of distributed data processing (e.g., Spark, Ray), workflow orchestration (e.g., Flyte/Union, Airflow), and columnar/lakehouse formats (e.g., Parquet, Iceberg).
Experience building self-service analytics products, semantic layers, or BI/dashboard tools for cross-functional users.
Business-level Japanese proficiency.
========================================================================= Notes ・Typically, all interviews are conducted via Google Meet. ・Job postings are currently available 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 curriculum vitae for any reason, we may request an English resume during the selection process depending on the position.
Compensation and Benefits ・Salary commensurate with experience and industry standards ・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, welfare pension insurance, industrial accident compensation insurance, employment insurance, nursing care insurance ・Housing allowance ・Retirement allowance system ・Car rental support ・Internal training programs (software learning, language learning)
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