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Senior 3D Computer Vision & LiDAR Engineer
Eliassen Group
- United States
- United States
Über
Rate: $80.00 to $95.00/hr. w2
Responsibilities
Architect an end-to-end Python/C++ pipeline that ingests .las/.laz and executes ground filtering, semantic segmentation, co-registration, and structural modeling.
Implement and tune VGICP and Pose Graph Optimization to stitch UAV and MLS datasets, correcting Z-axis drift and SLAM/IMU micro-errors.
Develop, train, and deploy 3D neural networks such as MambaNet/SSM, SparseConvNet, or PointNet++ for woody biomass versus foliage segmentation.
Apply geometric filtering including Cloth Simulation Filters and eigenvalue/covariance features to normalize terrain and isolate trunks.
Engineer watertight surface reconstruction using Screened Poisson to convert woody point clouds into meshes.
Compute empirical Above Ground Biomass using divergence theorem methods on large meshes with correct normal orientation.
Implement robust normal estimation and global orientation with methods such as MST-based or Laplacian smoothing prior to Poisson reconstruction.
Optimize large-scale processing through subsampling, voxelization, and GPU-accelerated tensor operations in cloud environments.
Experience Requirements
Expert Python development for high-performance, object-oriented data pipelines.
Strong C++ for performance optimization and potential CUDA kernel development.
Extensive Open3D experience for ICP, PGO, and geometric operations.
Proficiency with PDAL and laspy for LiDAR I/O and batch filtering; familiarity with CloudCompare CLI.
Expert PyTorch with 3D data; experience with PyTorch3D or PyTorch Geometric.
Ability to implement space-filling curves or voxel serialization for sequence models or 3D convolutions.
Deep knowledge of linear algebra including transformations, quaternions, covariance, and spatial indexing with KD-Trees and Octrees.
Understanding of LiDAR physics including SLAM versus IMU drift, beam divergence, incidence angles, and saturation effects.
Forestry and biomass modeling familiarity including TreeQSM or SimpleTree and the importance of angular diversity in trunk data.
Experience handling temporal and environmental variability across scans and imperfect alignment in real-world data.
5+ years in software engineering or ML research with 2–3 years focused on 3D point clouds, autonomous vision, or dense mapping.
Portfolio with custom ICP, 3D segmentation, or custom PyTorch data loaders for point clouds.
Education Requirements
MS or PhD in Computer Science, Geomatics, Remote Sensing, Robotics, or a related field.
Benefits (w2)
Medical, Dental, and Vision benefits.
401(k) with company matching.
Life insurance.
Equal Opportunity/Affirmative Action Employer Eliassen Group is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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Sprachkenntnisse
- English
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