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Senior Software Engineer, 3D Computer Vision

Field-ai
Irvine, USA
Full-time
Senior · 2+ years experience
Onsite
USD 135000-170000 yearly / year
Discovered 1 weeks ago
C++PythonPCLOpen3DEigenCeres
Free

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Full Job Posting

  • Develop and optimize point cloud processing pipelines, including registration, denoising, normal estimation, segmentation, and primitive extraction
  • Design efficient algorithms for large-scale, unstructured 3D datasets with attention to memory and runtime performance
  • Implement production-grade computational geometry and linear algebra in C++ and Python
  • Solve complex reconstruction challenges such as loop closure, global consistency, and multi-view fusion
  • Evaluate and integrate emerging 3D vision methods (e.g., neural implicit representations, advanced meshing techniques)
  • Partner with platform teams to ensure scalable, efficient deployment of algorithms
  • 2+ years of experience in Computer Vision, Computational Geometry, or 3D-focused Software Engineering
  • Master’s or Ph.D. in Computer Science, Applied Mathematics, or related field with specialization in 3D vision or geometric processing
  • Strong proficiency in modern C++ (C++14/17) and Python
  • Solid mathematical foundation in 3D geometry, linear algebra, rigid body transformations (SE(3), quaternions), and projective geometry
  • Deep experience with point cloud algorithms (ICP, GICP, RANSAC, NDT, region growing) and spatial data structures (k-d trees, octrees, voxel grids)
  • Hands-on experience with libraries such as PCL, Open3D, Eigen, or Ceres
  • Familiarity with common 3D data formats (PCD, PLY, E57, LAS)
  • Strong problem-solving skills and ability to translate academic research into production-ready code
  • Experience with non-linear optimization frameworks (Ceres, GTSAM, g2o) for bundle adjustment or pose graph optimization
  • Background in SLAM or Structure from Motion (SfM) pipelines
  • Experience processing LiDAR, RGB-D, or photogrammetry datasets
  • Familiarity with Linux development environments and containerization (Docker)
  • Exposure to ROS (not required)
  • Knowledge of survey-grade accuracy standards and georeferencing algorithms

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