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Remote Applied Intelligence Jobs in Virginia (NOW HIRING)

... and artificial intelligence to make value out of data. Provide consulting relating to the data ... Requirements: * MUST HAVE Six (6) years of relevant experience in applied research, big data ...

... and artificial intelligence to make value out of data. Provide consulting relating to the data ... Requirements: * MUST HAVE Six (6) years of relevant experience in applied research, big data ...

... intelligence, or applied research environments. * Strong knowledge of spectral phenomenology, imaging spectroscopy, and remote sensing principles. * Experience with image processing and scientific ...

Senior Hyperspectral Image Scientist

Springfield, VA · On-site +1

$92.30K - $166.85K/yr

... intelligence, or applied research environments. * Strong knowledge of spectral phenomenology, imaging spectroscopy, and remote sensing principles. * Experience with image processing and scientific ...

Senior Data Scientist

Mclean, VA · Remote

$150K - $200K/yr

... remote sensing analytics in support of intelligence and defense missions. Why Skyline Scientific ... Bachelor's degree in Image Science, Engineering, Applied Physics, Atmospheric Science, Applied ...

... artificial intelligence, cyber security as well as remote sensing applications. Position ... Bachelor's degree in Computer Science, Engineering, Physics, Applied Mathematics, Information ...

Product Optimization Senior Manager

Staunton, VA · Remote

$124.10K - $163.80K/yr

Daikin Applied is seeking a Product Optimization Senior Manager . The Product Optimization Senior ... Staunton, VA - Hybrid or Remote Your Responsibilities: * Manage and optimize product, pricing, and ...

GEOINT Analyst Mid

Charlottesville, VA · Remote

$110K - $150K/yr

Provides non-literal analysis to produce intelligence products, using remote sensing methodologies ... to be applied to challenging remote sensing problem sets. * Utilize analytic tools and techniques ...

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Remote Applied Intelligence information

What are the key skills and qualifications needed to thrive as a Remote Applied Intelligence professional, and why are they important?

To excel as a Remote Applied Intelligence professional, you need a solid background in data analysis, machine learning, and statistical modeling, often supported by a degree in computer science, statistics, or a related field. Proficiency in technical tools such as Python, R, SQL, cloud computing platforms, and relevant AI or data science certifications is highly valued. Strong problem-solving abilities, effective communication, and self-motivation are crucial soft skills for remote collaboration and project delivery. These competencies enable professionals to extract actionable insights from data, drive innovation, and succeed in a distributed work environment.

What are some common challenges faced by professionals in Remote Applied Intelligence roles, and how can they be addressed?

Remote Applied Intelligence professionals often encounter challenges such as ensuring effective collaboration across distributed teams, maintaining clear communication with stakeholders, and managing data security when working with sensitive information offsite. To address these issues, it's important to use secure, cloud-based collaboration tools, establish regular check-ins with colleagues, and follow best practices for data privacy. Staying proactive about communication and leveraging project management platforms can help remote team members stay aligned and productive.

What is a Remote Applied Intelligence job?

A Remote Applied Intelligence job involves leveraging artificial intelligence, machine learning, data analytics, and related technologies to solve business problems and drive decision-making, all while working from a remote location. Professionals in this field analyze large data sets, build predictive models, and develop intelligent solutions that can optimize processes, improve customer experiences, or uncover new business opportunities. The 'remote' aspect means the work is performed outside of a traditional office, offering flexibility and the ability to collaborate with global teams using digital tools.
What are the most commonly searched types of Applied Intelligence jobs in Virginia? The most popular types of Applied Intelligence jobs in Virginia are:
What are popular job titles related to Remote Applied Intelligence jobs in Virginia? For Remote Applied Intelligence jobs in Virginia, the most frequently searched job titles are:
What cities in Virginia are hiring for Remote Applied Intelligence jobs? Cities in Virginia with the most Remote Applied Intelligence job openings:
Infographic showing various Remote Applied Intelligence job openings in Virginia as of May 2026, with employment types broken down into 2% Internship, 79% Full Time, 9% Part Time, and 10% Contract. Highlights an 100% Remote job distribution.

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 13 days ago


Job description

Riverside Overview
Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country's most challenging technical problems.
All Riverside Research opportunities require U.S. Citizenship.
Position Overview
Riverside Research's Cognitive Intelligence Solutions Group (CISG) is seeking a Remote Sensing Engineer to support cutting-edge geospatial intelligence, autonomous sensing, and AI/ML-driven data exploitation efforts for the U.S. Department of Defense and Intelligence Community. The successful candidate will serve as a technical lead responsible for the automated verification and validation (V&V), test and evaluation (T&E), and performance assessment of remote sensing data pipelines, AI/ML models, and third-party vendor capabilities. This role bridges rigorous scientific methodology with production-grade engineering, enabling CISG to deliver validated, mission-ready geospatial intelligence products. The ideal candidate combines deep expertise in multispectral and hyperspectral remote sensing with hands-on experience applying machine learning to operational geospatial workflows.
This position is located in Fairfax, VA.
#LI-Onsite
Responsibilities
  • Design, develop, and implement automated V&V and T&E frameworks to assess the accuracy, performance, and operational readiness of remote sensing data products, AI/ML models, and vendor-delivered geospatial capabilities.
  • Lead the technical evaluation of commercial and government remote sensing platforms, sensors (multispectral, hyperspectral, SAR, LiDAR), and associated data products against mission-specific requirements.
  • Develop and maintain scalable, production-grade machine learning pipelines for geospatial applications including change detection, land cover classification, object detection, and environmental monitoring.
  • Apply state-of-the-art AI/ML techniques - including deep learning, transfer learning, self-supervised learning, and large vision/language models - to automate remote sensing data exploitation and analysis workflows.
  • Conduct rigorous uncertainty quantification, validation metric development, and statistical performance benchmarking across multi-source, multi-temporal geospatial datasets.
  • Architect and execute data quality assessment (DQA) protocols for ingested satellite, airborne, and in-situ sensor data; document and communicate findings to program teams and stakeholders.
  • Collaborate with program managers, government customers, and interdisciplinary engineering teams to translate operational requirements into validated technical solutions.
  • Evaluate and integrate emerging remote sensing technologies and open-source AI/ML frameworks; assess vendor claims, algorithm documentation, and technical data packages.
  • Contribute to IRAD initiatives advancing CISG's remote sensing and autonomous sensing capabilities, including development of novel approaches for environmental monitoring, target detection, and geospatial change analytics.
  • Author technical reports, white papers, and briefings documenting methodology, V&V results, and performance findings for government sponsors.
  • Provide technical mentorship to junior engineers and researchers on remote sensing methods, ML best practices, and geospatial data science.
  • Stay current with advances in foundation models, multi-modal geospatial AI, and emerging remote sensing sensor modalities relevant to national security applications.

Qualifications
Required Qualifications:
  • Active U.S. Citizenship (required for all Riverside Research positions).
  • Must be able to obtain and maintain a Top Secret security clearance with SCI access; ability to obtain program-specific clearances as required. Candidates with an active TS/SCI are strongly preferred.
  • Bachelor's degree in Remote Sensing, Geospatial Science, Earth Systems, Electrical Engineering, Computer Science, or a closely related STEM field.
  • A minimum of 8 years of related experience with a Bachelor's degree, 6 years with a Master's degree, 3 years with a PhD, or equivalent combination of education and experience. Graduate research experience counts toward this threshold.
  • Demonstrated expertise in multispectral and/or hyperspectral remote sensing data analysis, including atmospheric correction, spectral indices, spectral unmixing, and feature extraction.
  • Proficiency in Python for geospatial data engineering, including experience with rasterio, rioxarray, xarray, GDAL, geopandas, NumPy, and scikit-learn.
  • Hands-on experience with machine learning and statistical modeling applied to remote sensing or geospatial datasets (e.g., classification, regression, anomaly detection, change detection).
  • Experience developing and executing V&V or T&E processes for data products, software systems, or AI/ML models, including design of test plans, performance metrics, and acceptance criteria.
  • Familiarity with geospatial platforms and tools: ArcGIS Pro, QGIS, ENVI, and/or Google Earth Engine.
  • Experience with cloud-based geospatial workflows (AWS, Google Cloud, or Azure) and version control practices (Git/GitLab/GitHub).
  • Strong written and verbal communication skills with demonstrated ability to present complex technical findings to both technical and non-technical audiences.

Desired / Preferred Qualifications:
  • Active Top Secret/SCI clearance - candidates who already hold an active TS/SCI will be given strong preference and can expect an accelerated onboarding timeline.
  • Experience supporting DoD, Intelligence Community, or national security remote sensing programs (NRO, NGA, AFRL, ARO, or equivalent).
  • Familiarity with hyperspectral sensing platforms (e.g., AVIRIS, PRISMA, orbital hyperspectral systems) and hyperspectral analytics pipelines including mineral characterization and vegetation health assessment.
  • Experience applying deep learning frameworks (PyTorch, TensorFlow, Hugging Face) to geospatial or computer vision tasks, including fine-tuning foundation models or geospatial FMs (e.g., Prithvi, SatMAE, Clay).
  • Background in SAR processing, LiDAR analysis, or multi-modal sensor fusion for environmental or intelligence applications.
  • Experience with automated testing frameworks, CI/CD pipelines, and MLOps practices for geospatial AI/ML systems.
  • Track record of peer-reviewed publication, conference presentations (e.g., IGARSS, AGU, SPIE), or technical reports in remote sensing or geospatial AI.
  • Demonstrated experience in a lead or senior individual contributor role, including mentorship of junior technical staff and coordination across multi-disciplinary teams.
  • Familiarity with GEOINT tradecraft, NSDI standards, or DoD geospatial data standards (NTM, NITF, STANAG imagery formats).

Global Comp
$115,000 - $200,000 This represents the typical compensation range for this position based on experience, location and other factors.
Closing Statement
Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees.
Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran's status or any other status legally protected by applicable federal, state, and local law.