Orcrist

Overview

Develop geospatial and remote-sensing methods that turn imagery and spatial data into reliable analytical products using Python, machine learning, and deep learning architectures.

About Orcrist

Orcrist builds secure data intelligence software for defense, law enforcement, and enterprise teams. Our Sentinel platform combines data integration, AI-assisted analysis, and operational workflows. The GEOINT team is extending it with geospatial data services, remote-sensing capabilities, and a web-based common operational picture.

Requirements & Eligibility

• Formal university training in geoinformatics, remote sensing, Earth observation, applied mathematics, computer science, or a related discipline
• Substantial hands-on geospatial or remote-sensing experience
• Strong Python and scientific computing skills
• Practical machine-learning experience with scikit-learn and PyTorch or an equivalent framework
• Solid understanding of remote-sensing fundamentals
• Experience with satellite image analysis and at least one relevant task such as change detection, segmentation, object detection, or land-cover classification
• Sound statistical judgment
• Eligible to work in Germany

Key Responsibilities

• Develop change-detection workflows, including Sentinel-2 time series
• Build and evaluate object-detection, segmentation, and classification methods for satellite imagery
• Assess the suitability of different sensors, resolutions, acquisition conditions, and processing levels
• Design preprocessing and feature extraction with data engineers
• Combine raster outputs with vector and temporal data for spatial statistics, zonal analysis, and anomaly detection
• Build or source reference datasets and evaluation protocols
• Deliver traceable results with source references, timestamps, and uncertainty measures
• Package tested Python methods for repeatable batch processing or inference