Jobs at Woven by Toyota

Supports HR business partners and assigned business groups across employee relations, manager coaching, performance management, engagement, talent development, employee lifecycle activities, HR reporting, and process improvement. Maintains HRIS data, analyzes people metrics, manages assigned projects, applies employment policies and laws, and collaborates with cross-functional HR, legal, finance, and communications teams. Independently handles moderately complex HR matters while escalating sensitive issues appropriately.

Develop data strategies, scalable pipelines, automation, and evaluation processes for perception machine learning models used in AD/ADAS systems. Analyze large-scale data, improve camera-based computer vision performance, lead data initiatives, and collaborate across Toyota Group. The role requires data science, software engineering, cloud, database, and machine learning expertise, with hybrid work at the Nihonbashi office.

Lead end-to-end map data releases for autonomous driving, including specifications, vendor-data conversion, post-processing, quality verification, and delivery. Build ground-truth maps for machine learning, simulation, and system evaluation; manage vendor coverage, licensing, and data quality. Extend pipelines to urban roads and new map types, document processes, and mentor teammates. The role requires software or data engineering experience, large-dataset pipelines, programming proficiency, geospatial expertise, and cross-functional leadership.

Design, implement, and operate shared MLOps and LLMOps platforms supporting AI development, evaluation, deployment, monitoring, and releases. Build traceability, feedback loops, quality and safety monitoring, CI/CD automation, infrastructure-as-code workflows, observability, rollback mechanisms, and agent-based code review systems. Collaborate with product, ML, security, and cloud infrastructure teams to deliver reusable, reliable, secure, and sustainable AI platform capabilities. Hybrid work requires travel to Woven City several times per month.

Build and maintain scalable data infrastructure for autonomous-driving applications. Responsibilities include developing vehicle-fleet data ingestion pipelines, distributed cloud systems, data processing and transformation services, workflow orchestration, and reliable data platforms. Collaborate with computer vision and machine learning engineers to support large-scale ML development, validation, and simulation. The role requires strong Python or object-oriented programming, distributed application development, cloud experience, RPC protocols, testing, observability, and data pipeline expertise.

Establish and improve software quality assurance processes for automotive and automated-driving software. Responsibilities include defining development processes, supporting adoption, reviewing QA activities, auditing engineering projects, identifying non-compliance, preparing management reports, recommending corrective actions, and improving quality through automation tools. The role collaborates with developers, architects, testers, project managers, customers, and other stakeholders in a hybrid office environment.

Architects and extends core simulation technologies for autonomous driving and ADAS, including world engines, interfaces, schedulers, and agent frameworks. Integrates simulation software into validation workflows, analyzes simulated versus real-world performance, prioritizes improvements, partners with autonomy and release teams, supports roadmap planning, and promotes modern engineering practices. The role also involves designing software in Rust or C++, Python development, stakeholder collaboration, and mentoring developers.

Lead the design, development, optimization, and support of large-scale cloud-native data ingestion, storage, processing, and serving systems. Architect real-time systems in Python and C++, support autonomous-driving data platforms, collaborate with infrastructure and vehicle software teams, mentor junior engineers, and guide long-term product strategy. The role focuses on scalable data acquisition, edge filtering, distributed architectures, testing, and reliable production systems.

Build and support large-scale cloud-native data ingestion, storage, processing, and serving systems for autonomous driving. Develop real-time systems in Python and C++, design scalable distributed applications, and collaborate with data infrastructure, site reliability, and vehicle software teams. The role focuses on fleet data acquisition, edge filtering, validation, scenario detection, and production data pipelines across AWS-based environments.

Develop and continuously improve frontend software for a MaaS product and Mobility Service Controller. Responsibilities include building reusable React and TypeScript components, integrating interfaces, defining UI specifications, testing for defects and edge cases, reviewing code and documentation, and improving usability, accessibility, performance, and error handling. The role collaborates with product, design, backend, business, mobility partners, and Toyota-related services to translate operational needs into scalable user experiences.

Lead the design and development of perception foundation models for autonomous vehicles. Build deep learning systems for 3D scene understanding, sensor fusion, multimodal data analysis, training, evaluation, deployment, and inference optimization. Collaborate across perception, motion planning, simulation, infrastructure, and tooling teams while applying rigorous safety standards and agile practices.

Leads safety management and enterprise risk initiatives across autonomous vehicle and mobility programs. Responsibilities include developing the Safety Management System, facilitating safety committees, conducting hazard and risk assessments, maintaining safety and quality governance documentation, tracking corrective actions, supporting investigations, and reporting safety metrics to leadership. The role partners with engineering, operations, quality, legal, and compliance teams to strengthen safety culture and ensure compliant operational outcomes.

Lead strategy, discovery, roadmap, prioritization, requirements, and continuous improvement for a MaaS product connecting digital mobility services with real-world city operations. Collaborate with users, operators, municipalities, business, design, and engineering teams to validate hypotheses, define intuitive experiences, and scale the product from development through deployment. Use field research and generative AI to improve product decisions, prototyping, and execution.

As a Motion Planning Engineer, you will develop algorithms for AD/ADAS systems, focusing on path planning, vehicle motion control, and collaborative solutions with multiple teams. Responsibilities include creating ADAS features, ensuring software quality, and handling advanced research to development.

Design, develop, maintain, and deploy reliable backend services for the Robot Platform; improve test coverage, CI/CD, and monitoring; collaborate cross-functionally; monitor and troubleshoot production services and occasionally travel to Woven City for on-site maintenance.

Define vehicle-level AD/ADAS system requirements and decompose them into software subsystem requirements for Sensors, Planner, Perception, MAP, and HMI. Manage data-driven requirements, design system latency through scenario analysis, and define performance and functional product criteria. Collaborate with cross-functional stakeholders and design teams while applying automotive V-model processes for requirements derivation, tracking, and verification.

Leads the global Total Rewards strategy and operations covering compensation, benefits, payroll, equity, mobility, job architecture, governance, compliance, and executive compensation. Partners with senior leaders, Finance, Legal, HR, and regional teams to build scalable, equitable, data-driven programs. Oversees global vendors, annual compensation planning, benefits governance, payroll controls, communications, and international mobility. Manages and develops a distributed Total Rewards team while improving technology, analytics, data quality, operational efficiency, and employee understanding.

Lead a team of 7–8 engineers building and operating scalable ML training infrastructure. Own the technical roadmap, Kubernetes clusters, GPU fleets, distributed training, workflow orchestration, reliability, monitoring, and production support. Partner with machine learning, research, product, and platform teams to deliver secure, efficient infrastructure while mentoring engineers and strengthening engineering practices.

Senior HR Business Partner advising engineering leaders on talent strategy, organizational design, performance management, and change. Partners with COEs to deliver talent planning, development, engagement, compensation, and inclusion initiatives while coaching leaders and using data to measure employee experience.

Provide legal support for R&D, review and draft contracts in English and Japanese, manage document translations, and offer strategic legal advice for projects.