Remote Aperture Science Jobs in Virginia (NOW HIRING)

We are seeking an experienced SAR Data Scientist/Imagery Scientist to join a high-performing team supporting advanced AI and machine learning initiatives for complex national security and intelligence missions.

This program focuses on evaluating AI models against Government datasets to assess their performance, resilience, and robustness across a broad spectrum of adversarial scenarios. The effort also includes testing and validating autonomous algorithms designed to support operational decision-making in dynamic mission environments.

As a SAR Exploitation/Imagery Scientist, you will provide subject matter expertise in Synthetic Aperture Radar (SAR) imagery, geospatial analysis, and quantitative assessment to support data curation, imagery exploitation, and dataset development for machine learning model testing and evaluation. You will collaborate with engineers, data scientists, and mission analysts to ensure imagery products are prepared, standardized, and optimized for AI/ML applications.

Required Qualifications

• Active TS/SCI clearance with eligibility for CI Polygraph (we can sponsor your CI poly if you don't already have one)
• 4+ years of experience working with Synthetic Aperture Radar (SAR) imagery, including collection methodologies, radar phenomenology, image formation, and exploitation products.
• Experience evaluating SAR imagery quality metrics and interpreting sensor metadata, including the effects of collection geometry (e.g., graze angle, squint angle, azimuth) on SAR phenomenology.
• Demonstrated experience exploiting SAR imagery to detect, identify, and geolocate objects of interest.
• Strong understanding of remote sensing principles, imagery processing, and advanced SAR exploitation techniques.
• Excellent communication skills with the ability to effectively present SAR methodologies, imagery products, and analytical findings to both technical and non-technical audiences.

• Experience applying computer vision (CV), machine learning (ML), or deep learning techniques to SAR imagery and geospatial data to support intelligence, defense, or remote sensing applications.

• Support the Lead SAR Scientist in evaluating emerging sensor capabilities and comparing new collection platforms with existing operational systems.
• Assess the impact of new sensor data on existing data architectures, including metadata, file formats, schemas, APIs, and ETL processes required to ingest and integrate data into operational pipelines.
• Evaluate data acquisition strategies, expected collection latency, available data formats, and applicable security domains for new sensor sources.
• Develop preprocessing and standardization workflows to prepare imagery for labeling, analytics, and AI/ML model testing. This may include file format conversion, image tiling, geospatial normalization, and other data preparation activities to ensure compatibility with established data standards.