{"id":455624,"url":"https://alion.io/job/lionsbot-senior-software-engineer-path-planning","title":"SENIOR SOFTWARE ENGINEER (PATH PLANNING)","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":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":54000,"max_usd":103000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":131},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Gazebo","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Isaac Sim","optional":false},{"name":"Linux","optional":false},{"name":"Model Predictive Control","optional":false},{"name":"Motion Planning","optional":false},{"name":"Path Planning","optional":false},{"name":"Python","optional":false},{"name":"ROS2","optional":false},{"name":"RViz","optional":false},{"name":"SLAM","optional":false},{"name":"ROS","optional":true}],"status":"live","first_seen_at":"2026-09-05T09:38:26Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-30T23:57:07Z","board_verified":true,"closed_at":null,"days_open":55,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":55},"description":"Job Description\nWe are seeking a talented Software Engineer to develop advanced navigation and path planning algorithms that enable our global fleet of autonomous cleaning robots to move safely and intelligently in complex environments. This role is ideal for an engineer passionate about robotics, algorithm development, and system integration. You will take ownership of the planning stack, from high-level route planning, to complex complete path generation. This role demands strong fundamentals in motion planning, computational geometry, and optimization, as well as hands-on experience deploying algorithms on real robots. You will work closely with teams across SLAM, Perception, and Control to deliver navigation software that performs reliably in the real world.\nKey Responsibilities\nDesign and implement global path planning algorithms for large-scale dynamic environments, ensuring optimal and collision-free routing across multi-floor indoor environments\n\nDevelop and optimize complete coverage path planners tailored for cleaning robots\n\nDevelop and maintain costmap and environment representations, integrating perception and SLAM inputs for accurate planning\n\nDevelop and apply learning-based planning techniques (e.g. reinforcement and imitation learning) to enhance navigation adaptability and robustness in dynamic environments\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\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 navigation, motion or coverage planning.\n\nStrong proficiency in C++ and Python development on Linux.\n\nHands-on experience with ROS1 / ROS2 and modern software engineering practices.\n\nSolid understanding of robot kinematics, dynamics, and map representations (occupancy grids, costmaps, graph maps).\n\nDeep understanding of graph and sampling-based global planners (A*, D*, RRT*, PRM, etc.).\n\nExperience with implementing complete coverage path planning algorithms.\n\nFamiliarity with trajectory optimization and local planning frameworks (TEB, MPC, or similar).\n\nFamiliarity with simulation tools (Gazebo, Isaac Sim, or RViz) for development and validation.\n\nStrong analytical mindset with excellent problem-solving and debugging abilities.\n\nExperience with learning-based or hybrid planning algorithms (e.g. reinforcement and imitation learning) is a bonus.\n\nExperience with optimizing software for embedded hardware (e.g., Jetson, ARM) or GPU-based acceleration 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.","description_format":"text","description_chars":2948,"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":[],"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":13,"band":"cold","label":"Long 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