{"id":624353,"url":"https://alion.io/job/fieldai-senior-software-engineer-3d-computer-vision","title":"Senior Software Engineer, 3D Computer Vision","company":{"id":672883,"name":"FieldAI","domain":"fieldai.com","url":"https://alion.io/company/fieldai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":81,"open_postings":104,"ghost_share":0.231,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":62,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Irvine, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":240000,"currency":"USD","period":"year","gross":null,"usd_annual":240000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"Eigen","optional":false},{"name":"GTSAM","optional":false},{"name":"Linux","optional":false},{"name":"Open3D","optional":false},{"name":"Python","optional":false},{"name":"ROS","optional":false},{"name":"SLAM","optional":false}],"status":"live","first_seen_at":"2026-02-24T23:00:08Z","employer_posted_date":"2026-02-24","last_verified_at":"2026-10-30T08:13:52Z","board_verified":true,"closed_at":null,"days_open":247,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":246},"description":"Field AI is seeking a passionate Senior Software Engineer, 3D Computer Vision to play a vital role in the development of advanced algorithms for 3D reconstruction and spatial understanding. In this role, you will work with data from high-fidelity laser scanners and imaging sensors to design and optimize workflows for processing, analyzing, and structuring 3D point cloud datasets. The ideal candidate will have deep expertise in computational geometry and point cloud processing algorithms, delivering high-quality, maintainable code without necessarily requiring a background in robot hardware. Your contribution is essential to helping us extract precise geometric truths from the real world to ensure our continued growth and value.\nWhat You Get To Do\nDevelop and optimize point cloud processing pipelines, including registration, denoising, normal estimation, segmentation, and primitive extraction\nDesign efficient algorithms for large-scale, unstructured 3D datasets with attention to memory and runtime performance\nImplement production-grade computational geometry and linear algebra in C++ and Python\nSolve complex reconstruction challenges such as loop closure, global consistency, and multi-view fusion\nEvaluate and integrate emerging 3D vision methods (e.g., neural implicit representations, advanced meshing techniques)\nPartner with platform teams to ensure scalable, efficient deployment of algorithms\nWhat You Bring\n4+ years of experience in Computer Vision, Computational Geometry, or 3D-focused Software Engineering\nMaster’s or Ph.D. in Computer Science, Applied Mathematics, or related field with specialization in 3D vision or geometric processing\nStrong proficiency in modern C++ (C++14/17) and Python\nSolid mathematical foundation in 3D geometry, linear algebra, rigid body transformations (SE(3), quaternions), and projective geometry\nDeep experience with point cloud algorithms (ICP, GICP, RANSAC, NDT, region growing) and spatial data structures (k-d trees, octrees, voxel grids)\nHands-on experience with libraries such as PCL, Open3D, Eigen, or Ceres\nFamiliarity with common 3D data formats (PCD, PLY, E57, LAS)\nStrong problem-solving skills and ability to translate academic research into production-ready code\nWhat Sets You Apart\nExperience with non-linear optimization frameworks (Ceres, GTSAM, g2o) for bundle adjustment or pose graph optimization\nBackground in SLAM or Structure from Motion (SfM) pipelines\nExperience processing LiDAR, RGB-D, or photogrammetry datasets\nFamiliarity with Linux development environments and containerization 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