osapiens

Internship: Machine Learning (m/f/x)

osapiens Munich, Bavaria, Germany · €29K/yr

Software Development · 501-1,000 employees

Yesterday
machine-learning Junior (0-2 yrs) Full-time Temporary Germany
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About the role

You will train, evaluate, and deploy deep learning models on satellite imagery to detect deforestation within supply chains. You will also be responsible for taking prototype methods into production-ready code and collaborating with the team to improve model performance.

What they look for

Machine learning Deep learning PyTorch Python Computer vision Remote sensing Geospatial data Satellite imagery Data preparation Model evaluation Deployment Git Unix Software engineering Communication

Requirements

Candidates should be late-stage Bachelor's or Master's students in Computer Science, Electrical Engineering, or a related field. You must have strong foundational knowledge in machine learning, hands-on experience with PyTorch, and solid Python engineering skills.

Benefits

Purpose-driven mission Hands-on experience with geospatial AI Modern office environment Flexible hybrid work options Open team culture Flat hierarchies

Full description

Internship: Machine Learning (m/f/x)

Department: osapiens Terra

Employment Type: Fixed Term - Full Time

Location: Munich

Compensation: €2,410 / month

Description

This 6-month internship is part of osapiens Terra, a specialized team in Munich that combines remote sensing data and AI in sustainability software. We build enterprise software for deforestation-free supply chains. Our SaaS solution ensures compliance with the EU Deforestation Regulation (EUDR), which affects thousands of European companies and their suppliers. We track the supply chain end to end, from farmer to retailer, and use satellite data and deep learning to detect deforestation.

Our models run in production and are engineered to generalize across geographies, stay robust, and remain explainable. As an intern, you'll build and ship them with us.

Your 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

Your Experience

  • 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

Nice to have:

  • 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)

Join us for this and more...

  • 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.

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