{"id":455606,"url":"https://alion.io/job/lionsbot-lead-navigation-motion-planning-engineer","title":"Lead Navigation & Motion Planning Engineer","company":{"id":175194,"name":"LionsBot","domain":"lionsbot.com","url":"https://alion.io/company/lionsbot","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Kula","truth_index":null},"role":"Robotics","role_family":"Robotics","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["KR"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":108000,"max_usd":259000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":60},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Behavior Tree","optional":false},{"name":"BehaviorTree.CPP","optional":false},{"name":"C++","optional":false},{"name":"Linux","optional":false},{"name":"Model Predictive Control","optional":false},{"name":"Path Planning","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"ROS2","optional":false},{"name":"SLAM","optional":false}],"status":"live","first_seen_at":"2026-09-05T09:38:26Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-26T11:10:24Z","board_verified":true,"closed_at":null,"days_open":51,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":51},"description":"Job Description\nWe are seeking a talented Software Engineer to drive the development of advanced behavior, planning, and control strategies for our global fleet of autonomous cleaning robots. This role is ideal for an engineer passionate about robotics, algorithm development, and system integration. You will work on planning, real-time decision making and implement features such as multi-floor navigation and docking control systems. You will also work with other engineers to develop robust testing pipelines, aimed at ensuring quality and reliability of our robots.\nYou will own independent deliverables, collaborate closely with SLAM and Perception engineers, and play a critical role in shaping the next generation of autonomous systems. Key responsibilities include:\nKey Responsibilities\nDesign and implement modular behavior tree architectures for complex and robust robot decision-making.\n\nDevelop and optimize global planning algorithms (A*, D*, RRT*, PRM, etc.) for dynamic environments.\n\nDesign and tune local planners and controllers for smooth and safe robot motion (e.g. MPC, TEB, DWA)\n\nOptimize planning and control systems to ensure real-time system performance, including timing guarantees for control loops.\n\nCollaborate with SLAM and Perception engineers to align navigation with perception, mapping.\n\nDevelop comprehensive test cases for validating algorithms and software in both simulated and real-world environments, to ensure reliable performance.\n\nMaintain comprehensive documentation of all code implementations and test cases\n\nExplore advanced planning and control methods for real-world deployment (e.g., reinforcement learning-based planning)\n\nQualifications & Experience\nBachelor’s or Master’s degree in CS, Robotics, or a related field (or PhD with relevant focus)\n\n3+ years of industry experience in developing and deploying behavior, planning and control systems for autonomous robots.\n\nProficient in C++ and Python development on Linux.\n\nExperience working with ROS1 / ROS2.\n\nSolid foundation in data structures, algorithms, kinematics, dynamics, and control theory\n\nStrong understanding of robot dynamics, kinematics, and control theory.\n\nHands-on experience with behavior planning frameworks (e.g. BehaviorTree.CPP).\n\nStrong understanding of global and local path planning algorithms.\n\nFamiliarity with sensor modalities (e.g. LiDAR, RGBD cameras, IMUs)\n\nStrong attention to detail, with excellent problem-solving and debugging skills\n\nExperience with reinforcement learning applied to behavior, planning or control is a bonus.\n\nExperience with optimizing software for embedded hardware (e.g., Jetson, ARM) is a bonus.\n\nIf you have a passion for driving meaningful operational improvements, excel at analytical problem-solving, and thrive in a dynamic scaleup atmosphere, we invite you to join LionsBot and help shape the future of robotics innovation.\n*Only shortlisted candidate will be notified","description_format":"text","description_chars":2935,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"South Korea","iso":"KR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Robotic Software & Control Systems","Retail & Commercial Robotics","Service & Hospitality Robotics"],"lifecycle":[{"event":"open","at":"2026-09-06T09:38:26Z"}],"visa":[],"liveness":{"score":14,"band":"cold","label":"Long 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