Applied Geospatial ML Engineer

Vantor•Herndon, VA

About The Position

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. Vantor is a place for problem solvers, changemakers, and go-getters—where people are working together to help our customers see the world differently, and in doing so, be seen differently. Come be part of a mission, not just a job, where you can: Shape your own future, build the next big thing, and change the world. To be eligible for this position, you must be a U.S. Citizen. This position requires an active U.S. Government security clearance, applicants who do not currently hold the required clearance will not be eligible for consideration. Employment for cleared roles is contingent upon verification of clearance status. Export Control/ITAR: Certain roles may be subject to U.S. export control laws, requiring U.S. person status as defined by 8 U.S.C. 1324b(a)(3). Please review the job details below. This position requires an active U.S. Government Security Clearance at the TS/SCI level. Do you have a head for numbers and enjoy being an integral part of solving mission-critical, real-world problems? Do you like working with geospatial intelligence (GEOINT) data? If so, you’ll love working with us! Our solutions require innovative approaches that integrate bespoke capabilities and tools to solve our customers most complex challenges. We’re seeking an experienced AI/ML engineer to work across the full analytical workflow—from data acquisition and model development to pipeline evaluation, application prototyping, and hardware-based solution implementation.

Requirements

Must be a U.S. citizen with an active TS/SCI and the ability to obtain a CI polygraph.
B.S. in Data Science, Engineering, Math, Physics, Computer Science, or related field
5+ years designing, developing, testing, and deploying AI/ML models across diverse data types
Minimum 2 years of experience with low-shot learning, robust ML, spatial trajectory analytics, and cloud-based platforms (e.g., AWS, Azure) and AI/ML services (e.g., SageMaker, Watson Studio)
Experience working with remote sensing and geospatial datasets, including EO/SAR imagery, sensor-based data streams and familiarity with government collection platforms.
Experience with modern development practices, including version control, and CI/CD
Strong communication skills demonstrated through technical writing and speaking engagements (e.g., briefings, conference presentations), with excellent organizational skills and attention to detail
Competence with Linux environments

Nice To Haves

Advanced degree (M.S. or Ph.D.) in Data Science, Engineering, Math, Physics, Computer Science, or a related field
Proficiency with the Python data science stack (e.g., numpy, pandas, matplotlib, sklearn) and geospatial libraries (e.g., gdal, geopandas, shapely) or equivalent
Experience with a designing and implementing a wide variety of geospatial trajectory processing, analysis (e.g., forecasting), and visualization approaches
Ability to design and implement compute hardware and infrastructure solutions to support both client and backend AI/ML applications

Responsibilities

Contribute to multi-discipline AI/ML engineering teams using multi-INT data (with emphasis on GEOINT) to design, implement, and evaluate machine learning solutions
Engineer and transform diverse data types to support all phases of the AI/ML workflow
Architect, develop, and integrate novel AI/ML models (e.g., semantic activity detection, geospatial analytics, signal processing, and computer vision)
Design, implement, and assess various geospatial AI/ML solutions across hardware and software stacks
Stay current on AI/ML advances from industry and academia, applying them to government mission challenges
Provide subject matter expertise, mentoring, and strategic advice to government and internal teams on AI/ML trends, approaches, and delivery strategies
Communicate progress, results, risks, and challenges to government clients, partners, and project leadership
Support program execution by integrating diverse data science skillsets, managing sprint projections, assessing risks, and occasionally traveling for meetings and demonstrations