Kestrel Intelligence

AI-native platform for autonomous ISR tasking

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeCrystal City, Arlington, VA, USANo salary listed

About the Job

Requirements

Proven experience building geospatial data preprocessing pipelines for raster and vector data using the modern geospatial stack, including GDAL, SNAP, rasterio, and PostGIS.
Production-grade experience in at least two of the specified domains: traditional geospatial AI/machine learning (object detection or land classification, using tools such as scikit-learn or OpenCV); geospatial foundation models (such as AlphaEarth, Prithvi, or Clay); synthetic aperture radar and interferometry pipeline development (such as isce2); hyperspectral imaging processing (such as SPy); radio-frequency propagation modeling (such as CloudRF); digital elevation model handling in multiple formats (such as DTED); autonomous-system route planning (such as Auterion or ArduPilot); optimization of complex scheduling for satellite constellations or aircraft; or economic models for resource allocation such as auction, bidding, pricing, or waiting.
Must be a United States citizen.

Responsibilities

Architect and deploy production-grade subsystems that power products for commercial clients and national security missions.
Lead end-to-end creation of production-ready artificial intelligence, machine learning, and agentic subsystems.
Build robust preprocessing pipelines for raster and vector geospatial data using GDAL, SNAP, rasterio, and PostGIS.
Integrate emerging technologies, including geospatial foundation models and autonomous route planning, into a cohesive operational picture.

Desired Qualifications

Candidates based in the Colorado Springs, Colorado, or Washington, DC areas are a bonus; work may occur at customer sites in Crystal City, Virginia, and Herndon, Virginia.
Active Top Secret/Sensitive Compartmented Information clearance with a counterintelligence-scope or full-scope polygraph.

The Mission

At Kestrel, we are building the future of scalable autonomy across domains. Our systems enable commercial and national security customers to sense and act in support of complex missions without significant autonomous system expertise. This technology bridges domains (e.g., space, air, land, sea) and fields (e.g., AI, orbital dynamics, geospatial), requiring a team that has both breadth and depth in these related topics.

The Role

We are looking for an individual contributor to architect and deploy production-grade subsystems that power our cutting-edge products for both commercial clients and critical national security missions. As a Kestrel Data Scientist, you will lead the development of high-fidelity data processing pipelines, traditional AI/ML models, and wrapping them into tools for next-generation Agentic AI. You will work at the bleeding edge of geospatial science. This role requires adaptability, engineering rigor, and a deep respect for the mission.

Core Responsibilities:

- Architecture: Lead the end-to-end creation of production-ready AI/ML and agentic subsystems.

- Geospatial Engineering: Build robust preprocessing pipelines for raster and vector data (using GDAL, SNAP, rasterio, PostGIS).

- Innovation: Integrate emerging technologies, from Geospatial Foundation Models (GeoFMs) to autonomous route planning, into a cohesive operational picture.

You Must Be:

A master of foundational geospatial: Proven experience building geospatial data preprocessing pipelines (raster and vector) using the modern geospatial stack (GDAL, SNAP, rasterio, PostGIS, etc.).

A specialist: You must have production-grade experience in at least two (2) of the following domains:

- Traditional GeoAI/ML: Object detection/land classification (scikit, OpenCV, etc.).

- Geospatial Foundation Models: Utilizing GeoFMs like AlphaEarth, Prithvi, or Clay.

- SAR & Interferometry: Pipeline development (e.g., isce2).

- Hyperspectral Imaging: Processing (e.g., SPy).

- RF Propagation: Modeling signal data (e.g., CloudRF).

- Digital Elevation Models: Handling DEM in multiple formats (e.g., DTED).

- Autonomous Systems: Route planning for unmanned systems (e.g., Auterion, ArduPilot).

- Optimization: Complex scheduling for satellite constellations or aircraft.

- Economics: Models for resource allocation such as auction, bidding, pricing, waiting.

Must be a US Citizen

Bonus:

- Based in the Colorado Springs, CO or Washington, DC (working in customer sites in Crystal City, VA and Herndon, VA) areas

- Active Top Secret // Specially Compartmented Information (TS//SCI) clearance with counterintelligence-scope polygraph (CSP) or full-scope polygraph (FSP)

About the Company

Kestrel Intelligence

AI-native platform for autonomous ISR tasking

Kestrel Intelligence builds a software platform for managing intelligence, surveillance, and reconnaissance (ISR) in defense and commercial markets. It uses an AI-native orchestration system to dynamically allocate and prioritize sensor assets from multiple vendors, creating a marketplace for sensors and data. The product relies on agentic AI that can autonomously coordinate fleets of drones and ground robots based on human intent, enabling mission planning and acting at machine speed with tight multi-sensor integration. This approach differentiates Kestrel by combining proactive planning, cross-vendor orchestration, and a software-defined defense model to reduce operator workload and improve data quality. The company aims to ensure that intelligence is collected and synchronized effectively across global operations, delivering high-veracity, actionable insights to decision-makers.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Boise, ID
Founded: 2025

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