TIER IV

Develop and operate systems from in-car to cloud, focusing on backend and vehicle agent areas, with full-cycle ownership.

Builds an autonomous-driving MLOps platform, including model-training and monitoring pipelines, vehicle deployment, large-scale data analysis, sensor-data conversion, and model evaluation.

Develops simulation tools for autonomous driving, including mobile agents, scenario-language processing and generation, and sim-to-real gap analysis for vehicle, sensor, and traffic models.

Leads operational safety for autonomous-driving pilots and commercial operations, covering risk assessment, experiment processes, field requirements, incident analysis, and stakeholder coordination.

Define safety metrics for autonomous-driving systems and turn them into data requirements, pipelines, triage workflows, dashboards, and continuously updated safety cases.

Develops and productizes machine-learning planning for autonomous vehicles, evaluating algorithms with vehicle data and simulation. The role also integrates planning and control systems and optimizes real-time performance on in-vehicle ECUs.

Develop reusable autonomous-driving software for industrial and off-road vehicles, building core functions with C++ and ROS 2 and validating performance through simulation and field tests.

Builds and monitors medium-term and annual plans for TIER IV, analyzes markets, competitors, and technology trends, and advances M&A and capital-alliance opportunities.

Develop and operate edge infrastructure and middleware connecting in-car systems and cloud services, leading a development team.

Leads business planning and commercialization for an autonomous-shuttle OEM program, shaping revenue models, partner agreements and execution plans from demonstrations through production.

Leads division strategy and performance planning for an autonomous-driving business, covering market analysis, cross-functional projects, portfolio processes, budgeting, and executive reporting.

Manages safety reviews and operating controls for autonomous-driving experiments, including approvals, incident response, and improvements to the workflows governing vehicle tests.

Develop autonomous-driving software for industrial and off-road vehicles, from perception and planning algorithms to Autoware integration, simulation evaluation and field testing.

Owns accounting close and finance-process improvements, covering consolidated reporting, audit coordination, tax filings, internal controls, public-project accounting, and system automation.

Supports Web.Auto customers before and after adoption with product guidance, technical answers, implementation help, and sample code, coordinating with business development and product teams.

Own Pilot.Auto’s release lifecycle by building backend services, CI/CD pipelines, automated release gates, and traceable build and test workflows for autonomous-driving software.

Lead business development and project management to provide TIER IV products to domestic and international customers and partners.

Responsible for policy liaison work related to autonomous driving, including coordination with government agencies and industry stakeholders.

Lead market development for Co-MLOps project in automotive and mobility sectors, focusing on Japan and Asia.

Support legal operations related to contract reviews, project assistance, and legal risk management in a fast-paced environment.

Manage product development and strategy for autonomous driving software, including market research and partner management.

Support administrative functions for TIER IV's U.S. subsidiary and global portfolio companies, focusing on finance, accounting, and internal controls.

Responsible for developing and executing communication strategies and planning events to enhance brand recognition.

Engage in system engineering tasks for autonomous driving projects, defining operational domains and safety requirements.

Engage in system engineering tasks to develop autonomous driving systems, analyzing customer needs and regulations to define system and functional requirements.

Lead technical management from roadmap formulation to implementation and evaluation of autonomous driving system development.

Design and develop sensors and computing devices for autonomous vehicles, understanding requirements and specifications.

Lead projects in autonomous driving systems and services, managing requirements, KPIs, and technical direction.

Involved in all development phases of system design for autonomous vehicles, collaborating with various teams to develop TIER IV's autonomous vehicles.

Responsible for regulatory compliance, certification, quality assurance, and experimental management processes related to autonomous driving systems.

Manage and promote the overall project of autonomous vehicle development, collaborating with vendors and internal teams based on technical knowledge.

Develop sensing technologies for autonomous driving systems, including sensor system design and performance evaluation.

Design and develop planning and control technologies for autonomous driving, ensuring functionality in complex environments.

As an Autonomous Driving - Security Engineer, you will ensure the highest level of security by engaging with all stages of the development and operation lifecycle.

Lead validation efforts for AD/ADAS vehicle configurations and sensor evaluations, including project management and customer support.

Support project management for autonomous vehicle development, including meeting facilitation, tracking technical issues, and stakeholder coordination.

Provides technical support for autonomous-driving products, investigates issues across vehicles, sensors, and software, escalates findings, maintains technical documentation, and delivers customer training.

Analyze and visualize large datasets from autonomous driving operations, connecting information across teams.

Develop and implement Deep Neural Networks (DNN) for autonomous vehicles, focusing on hardware optimization and low power consumption.

Build an autonomous-driving software evaluation platform, automating scenario generation from fleet data, simulator integration, CI/CD testing, and test-result assessment.

Join as a System Software Engineer focusing on real-time performance for autonomous driving systems using Autoware.

Plans and implements testing for the Web.Auto platform supporting Autoware, covering test automation, CI/CD integration, performance improvement, and quality analysis for autonomous-driving systems.

Responsible for the design and operation of deployment infrastructure to support safe and rapid releases, and improve observability and continuous improvement of the release process.

Develop and operate the infrastructure supporting the evaluation of autonomous driving systems.

Organizes and tags TIER IV's collected data. A resume is mandatory; applicants are also asked for shareable links or materials on research, internships, or self-promotion.

As a senior backend engineer, you will lead your team technically and collaborate across teams to develop and maintain backend services for autonomous driving systems.

Join the development of open-source middleware that serves as the foundation for Autoware's autonomous driving system.

Design and develop autonomous systems for heavy machinery and construction equipment, focusing on both hardware and software aspects.

Lead the architecture design and implementation of a data platform for autonomous driving development, driving business impact through data-driven decision making.

Develop and operate a data platform that supports the collection, search, and analysis of data generated by autonomous driving.

Manage and advance domestic autonomous-driving implementation projects with municipalities and companies, coordinating vehicles, schedules, software settings, field trials, proposals, and team members.

In this role, you will be involved in backend design, development, testing, and operation of services that make up Web.Auto, considering the skills and preferences of applicants.

Develop high-performance and robust end-to-end machine learning models for autonomous vehicles.

Design, develop, integrate, and verify autonomous driving systems and related services based on the open-source software 'Autoware'.