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Field AI

Senior Software Engineer, 3D Computer Vision

Field AI · US · 137d ago
C++
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About the role


Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

What You Get To Do:

  • 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

    • What You Bring:

  • 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

    • What Sets You Apart:

  • 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

    • Tech stack

    C++
    Location US
    Posted 137d ago
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