Engineer, Robotics Algorithm (SLAM & LLM)

Blacksesame • Robotic Software & Control Systems • Processors, MCUs & AI Chips • Python • C++ • 17 days ago
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Salary
$54k – $75k per year (gross)
Location
In office (Singapore)
Employment
Full-Time

First seen by Alion on Sep 17, 2026.

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Blacksesame

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blacksesame.com • Warsaw • UTC+01:00 • Autonomous Driving • AI Chips & Accelerators • Processors, MCUs & AI Chips
Tech stack of Blacksesame

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.

Skills

Digital Mapping, Advanced Robotics, building robots, Technical Inspection, Spatial Data, Point Clouds, GPS Navigation, Vision, implementation skills, Autonomous Vehicles, Electrical Engineering, Algorithms, Mapping, Navigation Technology

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