Machine Learning Engineer - Geospatial AI

osapiens
München, Germany
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, German
Job source

Tech stack

Geographic Information Systems Artificial Intelligence Amazon Web Services Computer Vision Big Data Cloud Computing Code Review Computer Programming Distributed Computing Environment Python (Programming Language) Machine Learning Tensorflow
+8 more
Pytorch Deep Learning Backend Information Technology Data Management Machine Learning Operations Lidar Data Pipelines

Job description

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., * 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

Requirements

  • 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

Benefits & conditions

  • 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

About the company

Founded in 2018 and headquartered in Mannheim, Germany, osapiens works with around 2,500 companies in over 50 countries across industries such as consumer goods, automotive, fashion, pharmaceuticals, and medical products. The company is backed by Goldman Sachs and Decarbonization Partners, reinforcing its commitment to responsible, sustainable growth and has reached unicorn status in January 2026.

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