jobs in Black Sesame Technologies (Singapore) Pte Ltd

全职 Engineer, Robotics Algorithm (SLAM - LLM) 工作, 薪水, Black Sesame Technologies (Singapore) Pte Ltd 公司招聘中 - Ricebowl

Engineer, Robotics Algorithm (SLAM - LLM)

Black Sesame Technologies (Singapore) Pte Ltd

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

We are looking for a Robotics Algorithm Engineer to develop intelligent navigation and perception algorithms for autonomous robots operating in complex environments.

The 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.

Key Responsibilities

  • Develop and optimize LiDAR/ Vision/ IMU-based SLAM and localization algorithms.
  • Develop robust navigation solutions for dynamic and GPS-denied construction environments.
  • Work on point cloud registration, mapping, re-localization, loop closure, and map updating.
  • Integrate SLAM and navigation with ROS 2 and robotic platforms.
  • Develop LLM/VLM-based algorithms for robot scene understanding, task planning, and intelligent inspection.
  • Develop methods to combine BIM, spatial information, robot perception, and LLM/VLM for various applications.
  • Explore LLM/VLM-based agents, spatial reasoning, semantic mapping, and autonomous task generation.
  • Conduct algorithm testing, system integration, and deployment on real robots.

Requirements

  • Master’s degree or above in Robotics, Computer Science, AI, Automation, Electrical Engineering, or related fields.
  • Strong knowledge of SLAM, localization, mapping, or autonomous navigation.
  • Experience 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.
  • Experience with ROS/ ROS 2, C++ and Python.
  • Understanding of LLM, VLM, multimodal models, or AI Agent technologies.
  • Experience applying LLM/VLM to robotics, spatial intelligence, navigation, or embodied AI is highly desirable.
  • Strong problem-solving and hands-on implementation skills.

Experience with real-world robot deployment, publications, patents, or open-source robotics projects will be an advantage.

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