<div><b>About AiDASH</b></div><div><b> </b><span> </span></div><div><span>AiDASH is making critical infrastructure industries climate-resilient and sustainable with satellites and AI. Using our full-stack SaaS solutions, customers in electric, gas, water utilities, transportation, and construction are transforming asset inspection and maintenance - and complying with biodiversity net gain mandates and carbon capture goals. AiDASH exists to safeguard critical infrastructure and secure the future of humanAIty™. Learn more at </span><a href="http://www.aidash.com/">www.aidash.com</a><span>    </span></div><div><br /></div><div><span>We are a Series C climate tech startup backed by leading investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, Edison International, Lightrock, Marubeni, among others.  We have been recognized by Forbes two years in a row as one of “America’s Best Startup Employers.”  We are also proud to be one of the few climate software companies in Time Magazine’s “America’s Top GreenTech Companies 2024”. </span><a href="https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/topics/north-america-technology-fast-500.html?utm_source=bngaiwebsite&amp;utm_medium=referral&amp;utm_campaign=evolve-banner"><u>Deloitte Technology Fast 500</u></a><span>™ recently ranked us at No. 12 among San Francisco Bay Area companies, and No. 59 overall in their selection of the top 500 for 2024.  </span></div><div><span> </span></div><div><span>Join us in Securing Tomorrow!</span></div><div><br /></div><div><b>The Role</b></div><div><br /></div><div>We are looking for a <b>Senior Machine Learning Engineer</b> with deep expertise in <b>aerial LiDAR processing</b> and <b>3D computer vision</b>. In this role, you will be responsible for designing advanced ML models - including custom CNN and Transformer architectures - for large-scale 3D point clouds and multi-modal remote sensing data. </div><h3>How youll make an impact:</h3><ul><li>Design, implement, and optimize deep learning models for aerial LiDAR data - using CNNs, Transformers, and hybrid architectures</li><li>Build end-to-end pipelines for object detection, segmentation, and terrain modeling from geo-referenced point clouds</li><li>Combine aerial LiDAR with other data sources (e.g., RGB imagery, DSM/DTM, hyperspectral) using cross-modal transformers or fusion models</li><li>Implement efficient 3D spatial reasoning using voxel grids, sparse tensors, and attention-based architectures</li><li>Drive experimentation, model benchmarking, and ablation studies to push accuracy and efficiency boundaries</li><li>Collaborate with geospatial scientists and ML engineers to bring models to production via scalable APIs and cloud-native services</li><li>Apply MLOps practices to manage datasets, monitor model drift, and automate retraining workflows</li><div><br /></div></ul><h3>What were looking for:</h3><ul><li>5+ years of experience in applied machine learning or computer vision, with 3+ years focused on LiDAR or 3D data</li><li>Proven expertise in 3D deep learning (e.g., 3D CNNs, PointNet/PointNeXt, SparseConvNet, Minkowski Engine)</li><li>Experience building and fine-tuning transformer architectures for spatial or remote sensing applications (e.g., Swin3D, PointTransformer, GeoTransformer)</li><li>Strong coding skills in Python and deep learning libraries (PyTorch preferred)</li><li>Familiarity with aerial LiDAR data characteristics, including waveform/point density, elevation modeling, and coordinate systems (EPSG, UTM, etc.)</li><li>Hands-on experience with geospatial and point cloud libraries (PDAL, Open3D, PCL)</li><li>Understanding of GPU optimization and deployment in production (CUDA, TensorRT, TorchScript)</li><li>Master’s or PhD in Computer Science, Remote Sensing, Geomatics, or related field</li></ul><h3>Preferred Qualifications:</h3><ul><li>Experience with neural implicit models (e.g., NeRF, occupancy networks) for 3D scene modeling</li><li>Knowledge of spatiotemporal modeling or change detection from periodic LiDAR collections</li><li>Prior work with cloud-based pipelines (AWS SageMaker, GCP Vertex AI, or Azure ML)</li><li>Contributions to open-source geospatial/ML tools or research publications</li></ul><h3>What youll love:</h3><ul><li>Comprehensive Medical, Dental, and Vision Coverage: 100% coverage for employees and 80% for their spouses and children </li><li>Health Reimbursement Account (HRA): 100% funded by AiDASH to cover medical deductibles </li><li>401(k) Plan: Begin contributing after three months of employment to prepare for your future. Currently, no company match is offered </li><li>Parental Leave: Supportive parental leave with 16 weeks for primary caregivers and 4 weeks for secondary caregivers </li><li>Generous Vacation Policy: Accrue 20 vacation days per year, plus enjoy an additional flex holiday to celebrate whatever feels most important to you!</li><li>Winter Break: From December 25th through January 2nd, we give everyone time off to recharge and enjoy time with family and friends!</li></ul><div>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. </div><div><br /></div><div>We offer a competitive base pay range for this full-time position, which is between $140,000 and $190,000 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. </div><div><br /></div><div>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. </div>

AiDash

Senior LiDAR Engineer

AiDash