Machine Learning Engineer - Geospatial AI

Machine Learning Engineer - Geospatial AI

osapiens

Munich, Germany

About the role

As a Machine Learning Engineer (m/f/x), you will work on the machine learning systems powering our geospatial analytics platform. You will contribute to the development, deployment, and improvement of production ML models that analyze satellite imagery and detect environmental risks at scale. You will collaborate closely with product managers, software engineers, and geospatial experts to build scalable ML solutions that support real-world sustainability and compliance use cases. Your work may include improving existing deforestation detection models, developing new deep learning approaches for remote sensing data, and building reliable tooling and infrastructure for model training and deployment.

Your Responsibilities

• 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.

You may be a good fit if you

• 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.