Senior Software Engineer, 3D Computer Vision

Job description

[Field AI](https://www.fieldai.com/)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: - 4+ 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