Overview
A next-generation mobility company is looking for an engineer to help build the software stack that allows autonomous vehicles to plan safe paths and execute smooth, reliable control. You'd work across simulation, algorithm development, and real-world testing to push autonomous driving capability forward.
What You'll Work On
You'll join a team responsible for the vehicle's decision-making layers. Your day-to-day may include:
Designing, implementing, and improving planning algorithms such as behavior planning, route planning, motion planning, and trajectory optimization.
Developing control logic that enables vehicles to follow planned paths precisely under various road and environmental conditions.
Running experiments in simulation and on test vehicles, helping shape both architecture and tuning strategies.
Reviewing academic papers, reproducing key methods, and benchmarking competing approaches.
Debugging system behavior across sensors, localization, perception, planning, and control.
Working cross-functionally with teams focused on sensors, localization, safety engineering, testing, and vehicle integration.
Supporting open-source contributions for autonomous driving middleware and planning/control subsystems.
Required Skills & Experience
Strong programming skills in C++ and/or Python.
Experience building planning, navigation, or control algorithms in robotics, autonomous vehicles, or related fields.
Solid understanding of kinematics, dynamics, control theory, optimization, and numerical methods.
Familiarity with ROS or similar robotics frameworks.
Comfortable working in Linux environments.
Ability to read and discuss technical papers and translate them into practical implementations.
Effective communication in either Japanese or English.
Nice-to-Have
Experience with autonomous driving stacks, particularly motion planning or model predictive control.
Knowledge of vehicle dynamics, path tracking controllers, and safety-critical system behavior.
Practice with simulation tools, scenario-based testing, and real-world tuning.
Contributions to open-source robotics software.
Background in embedded systems or real-time computing.
Work Style & Environment
Hybrid work with flexibility in schedule.
Engineering-focused culture with an emphasis on research, testing, and continuous improvement.
Collaboration with a diverse, multidisciplinary team across software, robotics, and mobility engineering.
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