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Vantor jobs

Applied Geospatial ML Engineer - Herndon

$185,000 - 228,000
Vantor
Elden Street 733, Herndon
$185,000 - 228,000
Company Size icon
Company Size
5k+
Company Type icon
Company Type
Product
Exp Level icon
Exp Level
Senior
Job Type icon
Job Type
Full-Time
Language icon
Language
English
Visa sponsorship icon
Visa sponsorship
No

Requirements

Must:
- We require U.S. citizenship and an active TS/SCI security clearance, with the ability to obtain a CI polygraph. - We are seeking a bachelors degree in Data Science, Engineering, Mathematics, Physics, Computer Science, or a closely related discipline. - We need 5+ years of experience designing, building, testing, and deploying AI/ML models across varied data sources. - We require at least 2 years of hands-on experience with low-shot learning, robust machine learning, spatial trajectory analytics, and cloud platforms such as AWS or Azure, along with AI/ML services like SageMaker or Watson Studio. - We need experience working with remote sensing and geospatial datasets, including EO/SAR imagery, sensor-driven data streams, and familiarity with government collection systems. - We require experience with modern software development practices, including version control and CI/CD pipelines. - We need strong communication abilities demonstrated through technical writing and presentations, as well as excellent organization and attention to detail. - We require proficiency working in Linux-based environments. - We strongly prefer an advanced degree such as an M.S. or Ph.D. in a relevant technical field. - We prefer proficiency with the Python data science ecosystem, including numpy, pandas, matplotlib, and sklearn, plus geospatial tools such as gdal, geopandas, and shapely or equivalent libraries. - We value experience designing and implementing geospatial trajectory processing, analysis, forecasting, and visualization methods. - We prefer candidates who can design compute hardware and infrastructure solutions supporting both client-side and backend AI/ML applications.

Responsibilities

- We collaborate across multidisciplinary AI/ML teams using multi-INT data, with a strong focus on GEOINT, to design, implement, and evaluate machine learning solutions. - We engineer and reshape diverse data types to support every stage of the AI/ML workflow. - We architect, develop, and integrate innovative AI/ML models, including semantic activity detection, geospatial analytics, signal processing, and computer vision. - We design, implement, and evaluate geospatial AI/ML solutions across both hardware and software environments. - We stay informed on the latest AI/ML advances from industry and academia and apply those innovations to government mission needs. - We provide subject matter expertise, mentoring, and strategic guidance to government and internal stakeholders on AI/ML trends, implementation approaches, and delivery planning. - We communicate progress, outcomes, risks, and blockers clearly to government clients, partners, and project leadership. - We support program execution by combining data science expertise, managing sprint forecasts, assessing risk, and traveling occasionally for meetings and demonstrations.

Description


We are Vantor, and we are building the next frontier of spatial intelligence to help decision makers and operators understand what is happening now and prepare for what comes next. We are a mission-driven, collaborative team of problem solvers, changemakers, and self-starters working on meaningful challenges that help our customers see the world differently. This role offers a competitive base salary range of $185,000 to $228,000, a strong benefits package that includes a 401(k) match, mental health resources, student loan repayment assistance, adoption reimbursement, and pet insurance, and the opportunity to contribute to high-impact government work. This position requires U.S. citizenship and an active TS/SCI clearance, and it may be subject to U.S. export control requirements. We are an equal opportunity employer committed to an inclusive workplace where all qualified applicants are considered fairly.
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