SIL Environment Development Engineer, Autonomous Driving

About Woven by Toyota Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society. Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all. ========================================================================= TEAM Our team specializes in developing and advancing cutting-edge Software-in-the-Loop (SIL) environments to accelerate the evolution of autonomous driving technology. We utilize two key SIL environments, ClosedSILS and OpenSILS, leveraging their unique characteristics to efficiently evaluate and validate software. Additionally, we focus on addressing shared challenges, such as improving processing speeds, which are essential for enhancing development efficiency. In ClosedSILS, the simulator is connected to the autonomous driving software in real time, forming a feedback loop that enables dynamic evaluation of vehicle dynamics and control logic. This environment is designed with precision in mind, as we strive to improve the accuracy of simulation models while ensuring that generated signals are correctly linked to actual vehicle behavior. Furthermore, we are implementing computational optimizations and load reduction techniques to accelerate the simulation process. These enhancements aim to boost both the speed and reliability of testing, thereby significantly improving the overall development workflow. OpenSILS, on the other hand, leverages on-road driving log data to validate software behavior in an offline setting. A key focus here is achieving high fidelity in reproducing real-world phenomena, such as communication delays or processing delays caused by CPU load observed in physical environments. OpenSILS doesn't simply replay log data—it integrates adjustments based on the load and timing conditions recorded during real-world operation. This approach enables the environment to replicate situations under conditions that closely mirror those of the original vehicle. By doing so, we can analyze issues that occurred during physical testing, pinpoint underlying causes, and effectively drive improvements in software development. A shared challenge across both ClosedSILS and OpenSILS is the need for faster processing. By optimizing real-time capabilities within the simulation environments, we aim to deliver highly efficient testing platforms that drastically accelerate software development cycles. These ongoing initiatives address critical issues of safety and reliability in autonomous driving technology while laying the foundation for future-focused development. Our activities integrate simulation modeling, real-world data analysis, embedded system design, and comprehensive software development, creating an optimal environment for autonomous driving innovation. Working in this challenging yet rewarding setting will enable engineers to grow their skills while contributing to foundational advancements in next-generation mobility technology. WHO ARE WE LOOKING FOR? We are seeking driven individuals who are passionate about supporting the evolution of autonomous driving technology and actively contributing to the development and enhancement of SIL environments. We especially welcome candidates with the following skills and experience: Knowledge of Simulation Technology: Experience with simulation environments like ClosedSILS and OpenSILS, as well as constructing and utilizing feedback loops Data Analysis Skills: Expertise in leveraging real-world log data to accurately model and reproduce operational conditions such as load variance and processing delays Real-Time Optimization: Understanding of computational optimization and parallel processing techniques to achieve high-speed processing within SIL environments Commitment to Improving Accuracy: A deep understanding of simulation models and a drive to enhance the linkage precision between simulated signals and actual vehicle behavior In this role, you will be involved in thoroughly understanding how software logic translates into real-world vehicle performance, while contributing to solving safety and reliability challenges in the industry. By optimizing real-time capabilities and improving the accuracy of phenomena analysis, you will help build the foundation for next-generation autonomous driving technology. Our team environment is designed to integrate diverse expertise in computer science, embedded systems, control logic design, and simulation technology to tackle complex challenges. It is an ideal place for individuals who are eager to face new technical challenges and seek personal and professional growth as engineers. RESPONSIBILITIES Development and Improvement of ClosedSILS Environment Enhancing simulation model accuracy and developing signal mapping techniques Evaluating vehicle control logic through real-time feedback loops Optimizing systems to achieve faster processing for high-load operations Development and Improvement of OpenSILS Environment Developing technologies to accurately reproduce phenomena using real-world driving log data Designing and implementing methods to faithfully replicate load conditions and communication delays in virtual environments ※Either one of the above, or both Improving Processing Speed Across Both SIL Environments Enhancing real-time performance to accelerate feedback processing Reducing computational loads and optimizing parallel processing within simulation systems Strengthening Overall System Reliability Developing technologies to align the behaviors of virtual environments and real-world vehicle operations MINIMUM QUALIFICATIONS At least 3 years of experience implementing code in the C or C++ programming languages At least 3 years of practical experience in automotive software development or simulation development At least 3 years of practical experience working as part of a team on medium-scale or larger product development projects Practical experience working in both English and Japanese Conversational proficiency in Japanese NICE TO HAVES Experience developing autonomous driving systems and evaluation tools Experience designing and implementing large-scale infrastructure using cloud environments, on-premises servers, and other technologies Proficiency in system architecture design and development processes ========================================================================= Important Points ・All interviews will be arranged via Google Meet, unless otherwise stated. ・The same job descriptions are available in both English and Japanese; therefore, we kindly ask that you apply to only one version. ・We kindly request that you submit your resume in English, if possible. However, Japanese resumes are also acceptable. Please note that, depending on the English proficiency requirements of the role, we may request an English version of your resume later in the process. WHAT WE OFFER ・Competitive Salary - Based on experience ・Work Hours - Flexible working time ・Paid Holiday - 20 days per year (prorated) ・Sick Leave - 6 days per year (prorated) ・Holiday - Sat & Sun, Japanese National Holidays, and other days defined by our company ・Japanese Social Insurance - Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance ・Housing Allowance ・Retirement Benefits ・Rental Cars Support ・In-house Training Program (software study/language study) Our Commitment ・We are an equal opportunity employer and value diversity. ・Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.