Applied Geospatial ML Engineer

- We require U.S. citizenship and an active TS/SCI security clearance, with the ability to obtain a CI polygraph. - We need a bachelors degree in Data Science, Engineering, Math, Physics, Computer Science, or a closely related discipline. - We seek at least 5 years of experience designing, developing, testing, and deploying AI/ML models across varied data sources. - We require a minimum of 2 years working with low-shot learning, robust machine learning, spatial trajectory analytics, and cloud platforms such as AWS or Azure, including services like SageMaker or Watson Studio. - We look for hands-on experience with remote sensing and geospatial datasets, including EO/SAR imagery, sensor-driven data feeds, and familiarity with government collection systems. - We expect experience with modern engineering workflows, including version control and CI/CD practices. - We need strong communication skills demonstrated through technical writing, briefings, or conference presentations, along with excellent organization and sharp attention to detail. - We require proficiency working in Linux environments. - Preferred: an advanced degree such as an M.S. or Ph.D. in a relevant field. - Preferred: strong command of the Python data science ecosystem, including numpy, pandas, matplotlib, sklearn, and geospatial tools such as gdal, geopandas, and shapely or equivalent. - Preferred: experience building and implementing geospatial trajectory processing, analysis, forecasting, and visualization methods. - Preferred: ability to design compute hardware and infrastructure solutions that support client-facing and backend AI/ML applications.