{"id":1280884,"url":"https://alion.io/job/blacksesame-engineer-robotics-algorithm-slam-llm","title":"Engineer, Robotics Algorithm (SLAM & LLM)","company":{"id":39462,"name":"Blacksesame","domain":"blacksesame.com","url":"https://alion.io/company/blacksesame","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"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":{"min":5800,"max":8000,"currency":"SGD","period":"month","gross":true,"usd_annual":75168},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Autonomous Navigation","optional":false},{"name":"C++","optional":false},{"name":"Embodied AI","optional":false},{"name":"GTSAM","optional":false},{"name":"LIO-SAM","optional":false},{"name":"LLM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"ORB-SLAM3","optional":false},{"name":"Perception","optional":false},{"name":"Python","optional":false},{"name":"ROS","optional":false},{"name":"RTAB-Map","optional":false},{"name":"SLAM","optional":false},{"name":"VLM","optional":false}],"status":"live","first_seen_at":"2026-09-17T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-09-17T00:00:00Z","board_verified":false,"closed_at":null,"days_open":22,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":22},"description":"We are looking for a Robotics Algorithm Engineer to develop intelligent navigation and perception algorithms for autonomous robots operating in complex environments.\nThe role will focus on two key areas: SLAM/ autonomous navigation and LLM/VLM-based robotics intelligence, including spatial understanding, task reasoning, and BIM-aware robotic applications.\nKey ResponsibilitiesDevelop and optimize LiDAR/ Vision/ IMU-based SLAM and localization algorithms. \nDevelop robust navigation solutions for dynamic and GPS-denied construction environments. \nWork on point cloud registration, mapping, re-localization, loop closure, and map updating. \nIntegrate SLAM and navigation with ROS 2 and robotic platforms. \nDevelop LLM/VLM-based algorithms for robot scene understanding, task planning, and intelligent inspection. \nDevelop methods to combine BIM, spatial information, robot perception, and LLM/VLM for various applications. \nExplore LLM/VLM-based agents, spatial reasoning, semantic mapping, and autonomous task generation. \nConduct algorithm testing, system integration, and deployment on real robots. \nRequirementsMaster’s degree or above in Robotics, Computer Science, AI, Automation, Electrical Engineering, or related fields. \nStrong knowledge of SLAM, localization, mapping, or autonomous navigation. \nExperience with one or more SLAM frameworks or algorithms, such as FAST-LIO2, FAST-LIVO2, LIO-SAM, ORB-SLAM, RTAB-Map, ICP/GICP/NDT, or GTSAM. \nExperience with ROS/ ROS 2, C++ and Python. \nUnderstanding of LLM, VLM, multimodal models, or AI Agent technologies. \nExperience applying LLM/VLM to robotics, spatial intelligence, navigation, or embodied AI is highly desirable. \nStrong problem-solving and hands-on implementation skills. \nExperience with real-world robot deployment, publications, patents, or open-source robotics projects will be an advantage.\nSkills\nDigital Mapping, Advanced Robotics, building robots, Technical Inspection, Spatial Data, Point Clouds, GPS Navigation, Vision, implementation skills, Autonomous Vehicles, Electrical Engineering, Algorithms, Mapping, Navigation 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