Applied Geospatial ML Engineer - - Herndon
Core
Design, implement, and evaluate machine learning solutions for GEOINT using multi-INT data to support mission-focused government challenges.
Role type
Senior Applied Geospatial ML Engineer
Builds
Geospatial AI/ML solutions, semantic activity detection models, and signal processing pipelines for government clients.
Domain
Defense & Intelligence (GEOINT), Remote Sensing, Geospatial Analytics
Deliverable
production ML models
Required skills
Low-shot learning, resilient machine learning, spatial trajectory analytics, remote sensing (EO/SAR imagery), cloud platforms (AWS/Azure), CI/CD pipelines, Linux environments
Preferred skills
Advanced degree (M.S./Ph.D.), Python data science ecosystem (numpy, pandas, sklearn), geospatial libraries (gdal, geopandas, shapely), hardware infrastructure design, trajectory processing/forecasting
Technologies
AWS, Azure, SageMaker, Watson Studio, Linux, Python, numpy, pandas, matplotlib, sklearn, gdal, geopandas, shapely
Responsibilities
Architect and develop AI/ML models for semantic activity detection and computer vision; engineer diverse data formats for the AI/ML lifecycle; provide subject matter expertise and mentorship to internal teams and government partners; communicate progress and risks to government clients and leadership.
Seniority
Senior, hands-on IC with strategic guidance