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# Remote Sensing Software Engineer

- **Company:** Booz Allen Hamilton Inc.
- **Location:** Dayton, OH, United States
- **Experience:** Experienced
- **Salary:** $69,300.0 - $158,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Batch Processing, Cloud Computing, Continuous Delivery, Continuous Integration, Data Files, Geospatial Intelligence, Python (Programming Language), NumPy, OpenCV, Tensorflow, SciPy, Signal Processing, Software Engineering, Pytorch, Uncertainty Quantification (UQ), Orbital Mechanics, Gitlab, Kubernetes, Super-Resolution, Feature Extraction, Docker, Jenkins
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/remote-sensing-software-engineer-dayton-oh--12da1f60-5335-42fd-9c68-c551438786ea

## About the Role

Software Engineering, Artificial Intelligence (AI), Physics, Technical Delivery, Team Player, Software Development, Geometry, Signal Processing, Data Sets, IR (Infrared), * 4+ years of experience with remote sensing, image processing, or GEOINT data exploitation

 * Experience designing, modifying, developing, writing, and implementing software programming applications using Agile methods
 * Experience with Python and scientific Python packages such as NumPy, SciPy, OpenCV, or xarray
 * Experience with basic orbital mechanics
 * Experience with ML frameworks such as PyTorch or TensorFlow
 * Experience with large sensor datasets such as HDF5 or cloud object storage
 * Active TS/SCI clearance; willingness to take a polygraph exam
 * Bachelor's degree in a STEM field

Nice If You Have:

 * Experience with administration of continuous integration or continuous deployment (CI/CD) pipelines using Kubernetes, Docker, or Jenkins
 * Experience with sensor phenomenology, radiometric calibration, or remote sensing interpretation
 * Experience with super-resolution, deblurring, spectral exploitation, or resolved feature extraction
 * Experience with uncertainty quantification, Kalman filtering, or tracking algorithms
 * Experience with AI-augmented development workflows or agentic tools
 * Experience with GitLab-based CI/CD workflows
 * Master's degree in Physics, Mathematics, CS, or a related STEM field

## Description

At Booz Allen, you'll join a team using advanced imaging, physics-based modeling, and AI/ML to solve some of the nation's most compelling Space Domain Awareness (SDA) and remote sensing challenges. You'll contribute to the design and development of high-fidelity processing pipelines that transform raw sensor data into insight.

You'll join a collaborative technical delivery team where you'll contribute to secure, reliable, and user-centric tools that accelerate mission outcomes.

What You'll Do:

 * Develop software tools for radiometric modeling and satellite observation geometry.
 * Implement imaging and signal processing workflows, including motion compensation, multi-frame alignment, and super-resolution.
 * Build ML-enabled detection, anomaly identification, and object classification modules using operational EO/IR and synthetic datasets.
 * Design scientific Python pipelines such as NumPy, OpenCV, Astropy, or SciPy, for real time and batch processing.
 * Support orbital modeling tasks such as SGP4, TLE ingestion, or basic pose estimation.
 * Conduct imagery preprocessing such as radiometric calibration, artifact correction, and multi-frame filtering.
 * Maintain reproducible environments using GitLab, containers, and experiment-tracking tools.
 * Collaborate with astrodynamics SMEs, operations personnel, and ML engineers to deliver integrated mission capabilities.