Geospatial Solution Analyst - Machine Learning

We are seeking a Geospatial Solutions Analyst specializing in machine learning and artificial intelligence to develop advanced solutions for extracting, classifying, and analyzing information from geospatial data. This role will focus on applying machine learning, deep learning, and computer vision techniques to lidar point clouds, aerial imagery, elevation data, and other large geospatial datasets.

The successful candidate will work closely with geospatial analysts, software developers, and project teams to translate complex production requirements into accurate, scalable, and repeatable analytical solutions. This position requires a combination of geospatial expertise, applied machine learning experience, and the ability to move models from experimentation into operational production workflows.

• Design, develop, train, and evaluate machine learning and deep learning models for geospatial data analysis
• Develop automated methods for feature extraction, classification, segmentation, object detection, and change detection
• Work with lidar point clouds, aerial imagery, elevation models, and other raster and vector geospatial datasets
• Prepare, organize, and validate training, testing, and reference datasets
• Perform feature engineering and develop data-processing workflows that support model training and inference
• Evaluate model accuracy, generalization, uncertainty, and production readiness using appropriate quantitative and spatial validation methods
• Optimize models and inference workflows for large datasets and production-scale processing
• Integrate machine learning models into repeatable geospatial production workflows and internal software systems
• Research and evaluate emerging machine learning, computer vision, and geospatial AI technologies
• Collaborate with subject-matter experts and production teams to understand operational requirements and identify opportunities for automation
• Document model designs, datasets, assumptions, performance results, and implementation procedures
• Support the continued improvement, monitoring, and retraining of deployed models

• Bachelor’s degree in Geographic Information Science, Geography, Remote Sensing, Computer Science, Data Science, Engineering, or a related field
• Three to five years of professional experience involving machine learning, geospatial analysis, remote sensing, computer vision, or a related technical discipline
• Demonstrated experience developing and evaluating machine learning or deep learning models
• Proficiency in Python and commonly used data science and machine learning libraries
• Experience working with geospatial data, including raster, vector, imagery, elevation, or point-cloud datasets
• Understanding of supervised and unsupervised learning, model validation, feature engineering, data augmentation, and performance evaluation
• Experience preparing and managing training, validation, and testing datasets
• Strong understanding of coordinate systems, spatial data formats, data quality, and geospatial analysis concepts
• Ability to interpret model results spatially and communicate findings to technical and nontechnical stakeholders
• Familiarity with version control systems such as Git

• Strong analytical, problem-solving, documentation, and communication skills Preferred Skills

• Experience applying machine learning or deep learning to lidar, aerial imagery, satellite imagery, or other remotely sensed data
• Experience with point-cloud classification, image segmentation, object detection, feature extraction, or change detection
• Experience with machine learning frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn
• Familiarity with geospatial libraries and platforms such as GDAL, PDAL, Rasterio, GeoPandas, ArcGIS Pro, ArcPy, or similar technologies
• Experience working with convolutional neural networks, transformer-based models, multimodal models, or other modern computer vision architectures
• Experience processing large datasets using parallel, distributed, cloud, or GPU-accelerated computing
• Experience deploying models into operational or production environments
• Familiarity with MLOps practices, including experiment tracking, model versioning, reproducibility, monitoring, and retraining
• Experience with PostgreSQL, PostGIS, SQL, or other spatial data-management technologies
• Graduate-level education or research experience in machine learning, remote sensing, computer vision, geomatics, or a related discipline
• Experience working in a consulting, engineering, surveying, mapping, or geospatial production environment

Equal employment opportunity, including veterans and individuals with disabilities.

$80,000.00

Founded in 1994, Surveying And Mapping, LLC (SAM) is a nationwide leader in geospatial and construction-phase solutions. With more than 50 offices and 1,600 professionals, we deliver the scale, technology, and expertise needed to support projects of any size. SAM streamlines project delivery through a single, coordinated team, offering in-house capabilities across land surveying, aerial mapping, subsurface utility engineering (SUE), utility coordination (UC), GIS, BIM, and construction engineering inspection (CEI).

By combining advanced technology, digital workflows, and decades of experience, we provide accurate, actionable data that helps clients move critical infrastructure projects forward with confidence. At SAM, you’ll be part of a team that values innovation, growth, and the opportunity to make a tangible impact on the built environment.