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Technical excellence. Trusted solutions.
Remote Sensing Engineer
Location
Virginia
Posted
85 days ago
Salary
$115K - $200K / year
Seniority
Lead
Job Description
Remote Sensing Engineer
Riverside Research
• 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 • Collaborate with program managers, government customers, and interdisciplinary engineering teams to translate operational requirements into validated technical solutions • Author technical reports, white papers, and briefings documenting methodology, V&V results, and performance findings for government sponsors
Job Requirements
- Active U.S. Citizenship
- Must be able to obtain and maintain a Top Secret security clearance with SCI access; ability to obtain program-specific clearances as required
- 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
- 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.
Benefits
- Comprehensive compensation and benefit packages
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