Geospatial Solution Analyst - Machine Learning

SAM, LLC • ,

5d • Onsite

About The Position

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.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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

Benefits

• BlueCross BlueShield health insurance coverage begins the month after your hire date
• Dental plans available
• Free vision coverage for employees
• Company-paid premiums for Long-term disability/Life Insurance
• HSA + FSA plans
• SAM Cares program focused on holistic well-being
• Employee Referral Rewards Program of $1K, $2,500 or $5K
• Fidelity retirement plans with a 5% company match
• Tuition reimbursement
• Optional cellphone stipend
• Paid time off including vacation/sick/holidays
• Parental leave to support families
• Customized career development plan for licensing and certifications
• Project Manager Business Academy
• CAD Training Program
• Individual Development Plans/Career Check-Ins
• SAM WINS - our initiative for women-focused leadership and development
• Milestone Anniversary Recognition
• SAMbassador mentorship program
• Access to “Perks at Work” for discounts on wellness + travel + leisure and everyday purchases
• Company-sponsored events
• Free office snacks

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level