Develop, train, and improve machine learning models for geospatial and satellite imagery analysis
Contribute to the full ML lifecycle, including experimentation, evaluation, deployment, monitoring, and maintenance
Work on production systems that process large-scale satellite and geospatial datasets
Collaborate with ML engineers, backend engineers, product teams, and geospatial analysts to deliver reliable analytics products
Improve model performance, scalability, and robustness across different geographies and datasets
Build and optimize data pipelines, tooling, and workflows for efficient ML development
Apply modern deep learning and statistical techniques to remote sensing and environmental data
Support rapid experimentation while maintaining production reliability
Contribute to technical discussions, code reviews, and engineering best practices

Have a strong **quantitative background **in computer science, engineering, mathematics, remote sensing, or a related field
Have strong programming skills in Python and hands-on experience with modern deep learning frameworks such as PyTorch or TensorFlow
Hands-on experience with MLOps tools such as Weights & Biases, cloud infrastructure including Amazon Web Services, and/or high-performance computing environments
Feeling comfortable developing, training, and optimizing machine learning models in production environments
Communicate clearly and collaborate effectively across technical and non-technical teams
Have experience working with large datasets and distributed data processing workflows
Work effectively with AI-assisted development and coding tools
Are fluent in English (C1+). German skills are a plus

**Nice to have

Experience with computer vision tasks such as segmentation, classification, change detection, or time-series analysis
Experience working with remote sensing or satellite data (SAR, optical, LIDAR)
Familiarity with geospatial data processing libraries and tools
Experience deploying ML systems into production environments
Understanding of environmental, climate, or sustainability-related use cases
Experience translating complex business or regulatory requirements into data-driven solutions

The opportunity to work on meaningful technology with real-world environmental impact
A highly technical and collaborative team environment
Modern ML infrastructure and large-scale geospatial datasets
Ownership and growth opportunities based on your experience and interests
Flexible working environment in our Munich office near Sendlinger Tor
Competitive compensation and benefits

Machine Learning Engineer – Geospatial AI

Key skills