Senior LiDAR Engineer

How you'll make an impact:

• Design, implement, and optimize deep learning models for aerial LiDAR data - using CNNs, Transformers, and hybrid architectures
• Build end-to-end pipelines for object detection, segmentation, and terrain modeling from geo-referenced point clouds
• Combine aerial LiDAR with other data sources (e.g., RGB imagery, DSM/DTM, hyperspectral) using cross-modal transformers or fusion models
• Implement efficient 3D spatial reasoning using voxel grids, sparse tensors, and attention-based architectures
• Drive experimentation, model benchmarking, and ablation studies to push accuracy and efficiency boundaries
• Collaborate with geospatial scientists and ML engineers to bring models to production via scalable APIs and cloud-native services
• Apply MLOps practices to manage datasets, monitor model drift, and automate retraining workflows

What we're looking for:

• 7+ years of experience in applied machine learning or computer vision, with 3+ years focused on LiDAR or 3D data
• Proven expertise in 3D deep learning (e.g., 3D CNNs, PointNet/PointNeXt, SparseConvNet, Minkowski Engine)
• Experience building and fine-tuning transformer architectures for spatial or remote sensing applications (e.g., Swin3D, PointTransformer, GeoTransformer)
• Strong coding skills in Python and deep learning libraries (PyTorch preferred)
• Familiarity with aerial LiDAR data characteristics, including waveform/point density, elevation modeling, and coordinate systems (EPSG, UTM, etc.)
• Hands-on experience with geospatial and point cloud libraries (PDAL, Open3D, PCL)
• Understanding of GPU optimization and deployment in production (CUDA, TensorRT, TorchScript)
• Master’s or PhD in Computer Science, Remote Sensing, Geomatics, or related field

Preferred Qualifications:

• Experience with neural implicit models (e.g., NeRF, occupancy networks) for 3D scene modeling
• Knowledge of spatiotemporal modeling or change detection from periodic LiDAR collections
• Prior work with cloud-based pipelines (AWS SageMaker, GCP Vertex AI, or Azure ML)
• Contributions to open-source geospatial/ML tools or research publications

What you'll love:

• Comprehensive Medical, Dental, and Vision Coverage: 100% coverage for employees and 80% for their spouses and children
• Health Reimbursement Account (HRA): 100% funded by AiDASH to cover medical deductibles
• 401(k) Plan: Begin contributing after three months of employment to prepare for your future. Currently, no company match is offered
• Parental Leave: Supportive parental leave with 16 weeks for primary caregivers and 4 weeks for secondary caregivers
• Generous Vacation Policy: Accrue 20 vacation days per year, plus enjoy an additional flex holiday to celebrate whatever feels most important to you!
• Winter Break: From December 25th through January 2nd, we give everyone time off to recharge and enjoy time with family and friends!

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.

We offer a competitive base pay range for this full-time position, which is between $190,000 and $230,000 per year. This range reflects the anticipated base salary for new hires. We strive to ensure our compensation packages are equitable and aligned with industry standards. Your recruiter can share more about compensation during the hiring process.

We are committed to providing an inclusive and accessible interview experience for all candidates. Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs.