Internship: Machine Learning (m/f/x)

Key Responsibilities

• Train, fine-tune, and evaluate deep learning models on satellite imagery using PyTorch
• Evaluate the performance of existing models and maps, find where they fail, and fix it
• Read and implement recent computer vision and remote sensing papers, and turn them into working code
• Take prototype methods to production-ready code that scales across large geospatial pipelines
• Own a project end to end: from data preparation and training through evaluation and deployment
• Write clean, efficient, tested, and well-documented code in a shared codebase
• Share ideas for new models and algorithms, and explain your work clearly to the team

Skills, Knowledge & Expertise

• Late-stage Bachelor's or Master's student in Computer Science, Electrical Engineering, or a related field
• Strong foundation in machine learning concepts and algorithms
• Hands-on experience building and training deep learning models in PyTorch (projects, thesis, research, or prior internships)
• Solid Python engineering skills: you write maintainable code, use Git, and are comfortable on Unix-based systems
• Ability to read research papers and turn them into implementations
• Excellent English and communication skills
• You work independently, take ownership, and are just as comfortable in a team
• Curiosity and a drive to learn new things quickly

• Computer vision research experience
• Experience with satellite imagery or geospatial data (multispectral imagery, GeoTIFFs, GeoJSON, rasterio/GDAL, etc.)
• Experience scaling training or inference (GPUs, distributed training, cloud environments)

Benefits

• A purpose-driven mission tackling complex sustainability challenges while working alongside global industry pioneers at a fast-growing unicorn company
• Real-world, unsolved problems in geospatial AI and remote sensing
• Hands-on experience across the full ML lifecycle: data, training, evaluation, and deployment
• Your work ships. If your model performs well enough, it goes into production and reaches 2,500+ customers
• A modern Munich office with flexible hybrid work options, open team culture, and flat hierarchies.