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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.

• 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.

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).

$115,000 - $200,000 This represents the typical compensation range for this position based on experience, location and other factors.

 
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.
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