Quick overview
Job description
What You Get To Do
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Design and develop scalable LiDAR mapping algorithms to support autonomous robot operations.
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Improve the accuracy, robustness, and scalability of point cloud processing pipelines used in online and offline mapping systems.
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Deploy large-scale mapping systems and data processing pipelines in production and ensure efficient and quality customer deliverables.
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Validate mapping systems and algorithms through testing on real robots and in large-scale unstructured environments.
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Collaborate cross-functionally to meet project-specific documentation requirements and customer expectations.
What You Have
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Master’s degree or Ph.D. in Computer Science, Engineering, or a related field, with expertise in robotics and 3D computer vision.
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Proficiency in C++ and Python, with a proven ability to write maintainable and efficient code in production.
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Solid theoretical knowledge of 3D geometry, computer vision and robot kinematics.
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Solid understanding of point cloud data structure and related algorithms (e.g., ICP, NDT).
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Experience with LiDAR SLAM algorithms and optimization tools such as Ceres, GTSAM, or g2o.
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Hands-on experience with tools and libraries such as PCL, Open3D, Autoware.
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Familiarity with Robot Operating System (ROS) and software development practices in Ubuntu.
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Familiarity with LiDAR systems and 3D data formats (e.g., PCD, PLY, E57, LAS).
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Strong problem-solving skills, attention to detail, and able to work independently while managing multiple priorities.
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Strong work ethic, highly self-motivated, and excellent written and verbal communication skills.
The Extras That Set You Apart
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Research experience with publications in top-tier robotics, computer vision, or machine vision venues
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Familiarity with tools such as CloudCompare, Leica Cyclone, Faro Scene, or Trimble RealWorks
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Familiarity with geospatial data, georeferencing, and coordinate systems
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Experience with survey control, calibration workflows, or on-site measurement tools (e.g., total stations)
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