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AI Flood Inundation Nowcasting Engineer

Violet Adeyemi

Full-time · Job · Amsterdam

About the role

Our mission is simple to state and hard to deliver: give communities a few more hours of warning before water reaches their streets. Physical hydraulic models are accurate but take hours to run, which is too slow when a storm cell stalls over a river basin. Paleon Data is building learned surrogate models that predict flood extent at street-level resolution in minutes, using rainfall radar, river gauges and terrain data. You'll lead the modelling work on this nowcasting system, starting with three pilot basins in the Netherlands and Bangladesh. The team is small, the data is real, and the people using your forecasts are municipal emergency planners and humanitarian responders rather than advertisers.

Responsibilities

  • Design and train surrogate models for flood extent and depth from radar and gauge inputs
  • Validate predictions against historical flood events and satellite-derived inundation maps
  • Quantify uncertainty so emergency planners understand forecast confidence
  • Work with partner NGOs to shape how forecasts are delivered in the field

Requirements

  • Experience building spatio-temporal deep learning models, ideally for geophysical data
  • Comfortable with gridded datasets, raster processing and large NumPy arrays
  • Statistical rigour in evaluating rare, high-impact events
  • Motivated by climate adaptation work

Benefits

  • Remote within UTC-1 to UTC+6
  • Four-day work week option after probation
  • Mission-aligned work with humanitarian partners
  • Generous parental leave

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch numpy pandas gcp

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