募集要項
- 仕事内容
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・Lead the design, implementation, and optimization of decision-making, path planning, trajectory generation, and speed planning algorithms for autonomous trucking scenarios.
・Define the architecture, interfaces, data contracts, and performance requirements of the planning module from a full-system perspective.
・Collaborate with perception, prediction, and control teams to improve planning robustness under perception uncertainty, dynamic traffic interaction, and vehicle dynamics constraints.
・Drive algorithm iteration through simulation, log replay, closed-course testing, and road-test feedback.
・Lead a team of planning engineers, including technical direction setting, design review, code review, task decomposition, and engineering quality control.
・Translate research or prototype-level methods into production-quality C++ software that can be tested, debugged, integrated, and maintained in a real-time autonomous driving stack.
- 応募資格
-
- 必須
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・Strong experience in autonomous driving planning, including motion planning, path planning, behavior planning, trajectory optimization, or speed planning.
・Deep understanding of MPC, convex optimization, and numerical optimization, with hands-on experience applying optimization methods to real autonomous driving or robotics systems.
・Strong C++ programming capability, with the ability to build reliable, maintainable, and performance-aware algorithm software.
・Experience defining module boundaries and interfaces across perception, prediction, planning, and control in a complex robotics or autonomous driving system.
・Proven experience as a Tech Lead or engineering manager, including leading a team, reviewing technical designs, mentoring engineers, and driving delivery quality.
- 歓迎
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・Experience with autonomous trucks, commercial vehicles, or high-speed highway autonomous driving scenarios.
・Experience with ROS or ROS2 development in robotics or autonomous driving systems.
・Familiarity with search-based planning methods such as Hybrid A*, State Lattice, MCTS, or graph-search variants.
・Familiarity with decision-making under uncertainty, including MDP, POMDP, reinforcement learning, inverse reinforcement learning, or probabilistic graphical models.
・Experience with modern control methods, including nonlinear control, optimal control, and vehicle dynamics modeling.
・CUDA or GPU acceleration experience for planning, optimization, simulation, or performance-critical workloads.
- 雇用形態
- Full Time / 正社員
- 勤務地
- 東京都
- 勤務時間
- フレックスタイム制（コアタイムあり）
- 年収・給与
- 1500万円～2499万円
- 待遇・福利厚生
- Employment Insurance / 雇用保険,Industrial Accident Compensation Insurance / 労災保険,Employees' Pension Insurance / 厚生年金保険,Employees' Health Insurance / 健康保険
- 休日休暇
-
[勤務時間]
フレックスタイム制（コアタイム あり）
リモートワーク ：要相談
[休日・休暇]
土・日・祝日
年次有給休暇
慶弔休暇、産休・育休等"
