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Work with Us

We build the tools institutions rely on to understand our planet — from satellite archives to forecasting platforms. If that sounds like your kind of problem, we’d love to hear from you.

You'll design and maintain the ingestion and processing pipelines that transform raw satellite, climate, and geospatial data into ready-to-use products for our institutional platforms.

You'll work closely with our AI and Applications teams to make sure large, messy, heterogeneous datasets become something reliable, fast, and easy to build on.

What you’ll do

  • Design, build and operate large-scale EO/climate data pipelines

  • Work with Sentinel, Copernicus and other public satellite archives

  • Optimize storage and access patterns for large geospatial datasets

  • Collaborate with AI engineers to prepare data for ML pipelines

What we’re looking for

  • Solid experience with Python and geospatial libraries (GDAL, rasterio, xarray)

  • Comfortable with cloud or on-prem data infrastructure (S3-compatible storage, Docker)

  • Understanding of raster/vector data formats and coordinate systems

  • Good spoken and written English

Nice to have

Experience with Copernicus / ESA data products
Familiarity with STAC catalogs
Background in remote sensing or earth observation

You'll design and train machine learning models applied to satellite, climate and geospatial data, supporting use cases like monitoring, forecasting and anomaly detection across multiple domains.

Your work will feed directly into the digital platforms institutions and space agencies rely on for evidence-based decisions.

What you’ll do

  • Design, train and evaluate ML/DL models on geospatial and time-series data

  • Bring research prototypes into production-grade pipelines

  • Work with the data team to define feature pipelines and datasets

  • Document experiments and communicate results to non-technical stakeholders

What we’re looking for

  • Strong Python skills and experience with PyTorch or TensorFlow

  • Solid grasp of ML fundamentals and model evaluation

  • Experience working with large, real-world (i.e. messy) datasets

  • Good spoken and written English

Nice to have

Experience with remote sensing or time-series forecasting
Familiarity with MLOps tooling
Publications or open-source contributions

You'll build the web interfaces and dashboards that let institutions, agencies and end users explore and understand large volumes of satellite and climate data — clearly, quickly, and without a manual.

You'll work across the stack with our data and AI teams to turn complex outputs into something genuinely usable.

What you’ll do

  • Build responsive, accessible interfaces for data-heavy web platforms

  • Work with maps, charts and large datasets without sacrificing performance

  • Collaborate with design and backend teams on API contracts

  • Contribute to our shared component library and coding standards

What we’re looking for

  • Strong experience with React and TypeScript

  • Comfortable with modern CSS and responsive/animated UI

  • Attention to detail on accessibility and performance

  • Good spoken and written English

Nice to have

Experience with map libraries (MapLibre, Leaflet, deck.gl)
Experience with Next.js
An eye for motion design and micro-interactions

Don’t see the right role?

We’re always open to meeting people who’d be a great fit for MEEO — send us a spontaneous application.

MEEO S.r.l.

Meteorological Environmental Earth Observation

Registered office: Via Antonio Frizzi 21, 44121 Ferrara (FE), Italy
VAT and tax code: IT01629630383 · REA: FE-184122 · Share capital: €15,000.00 fully paid up

© 2026 MEEO. All rights reserved.

Ever wondered what a satellite sees that you don’t? .

Coming up in space history

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Neptune is found

23 September · 180 years · tomorrow

Johann Galle spots it within one degree of where Le Verrier's mathematics said it would be.