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Noéa is an affective-AI platform that translates hydrological data—precipitation, floods, glacier mass loss—into emotionally legible outputs (valence–arousal) that drive immersive, multi-user XR. We’re a fast-growing, mission-driven team blending environmental science, machine learning, and experiential design to make climate signals felt, not just seen.
Website
https://www.meetingofwaters.org/noea
The Role
Own the end-to-end ML stack for three domains—atmosphere (precipitation), rivers (flood), glaciers (mass loss)—and ship an interpretable pipeline that runs in production. You’ll design data ingestion and feature extraction, train unsupervised & hybrid models, quantify uncertainty, and expose clean APIs that feed a real-time visual engine. Expect close collaboration with artists and scientists, rapid iteration, and a bias for elegance, traceability, and performance.
What you’ll do
• Build robust pipelines for time-series & gridded data (gauges, reanalysis, remote sensing; xarray/rasterio/geopandas).
• Engineer features: intensity, variability, anomalies, return periods; discharge/soil/topography; mass balance/elevation/albedo.
• Train clustering/representation/sequence models; calibrate valence/arousal mappings; write model cards & uncertainty notes.
• Serve outputs via lightweight APIs/WebSockets; optimize for low latency and low power; maintain reproducibility (DVC/CI).
• Collaborate across disciplines to translate model signals into human-centered interaction and clear narratives.
You’re a fit if you have
• Strong Python + ML (PyTorch/Lightning or JAX; scikit-learn) and time-series/geospatial skills (xarray, rasterio, geopandas).
• Data engineering/MLOps hygiene (Pydantic, DVC, Prefect/Airflow; conda/poetry, Docker, CI).
• Bonus: hydrology/remote sensing (ERA5/IMERG/GLOFAS/ICESat-2), explainability, XR data interfaces (Unity/WebSocket/HTTP).
• Interdisciplinary fluency: you communicate with scientists, artists, curators, and policymakers; you value accessibility, ethics, and inclusive design; you write crisp docs and you ship.
Why this is so special
Greenfield responsibility, real datasets, public impact. Your models power an experience people remember—and act on. Small team, high trust, creative latitude, and an open, modular platform communities can adapt with local water data.
How to apply
Email [email protected] with subject “AI Engineer — Noéa” with the following:
1. Motivation letter and a brief design plan (how you’d approach the pipeline),
2. CV / LinkedIn
Only selected candidates will be contacted.
Meeting of Waters is an equal-opportunity, access-first team. We welcome diverse backgrounds, languages, and lived experiences—especially across the Global South and riverine communities.
Website
https://www.meetingofwaters.org/noea
The Role
Own the end-to-end ML stack for three domains—atmosphere (precipitation), rivers (flood), glaciers (mass loss)—and ship an interpretable pipeline that runs in production. You’ll design data ingestion and feature extraction, train unsupervised & hybrid models, quantify uncertainty, and expose clean APIs that feed a real-time visual engine. Expect close collaboration with artists and scientists, rapid iteration, and a bias for elegance, traceability, and performance.
What you’ll do
• Build robust pipelines for time-series & gridded data (gauges, reanalysis, remote sensing; xarray/rasterio/geopandas).
• Engineer features: intensity, variability, anomalies, return periods; discharge/soil/topography; mass balance/elevation/albedo.
• Train clustering/representation/sequence models; calibrate valence/arousal mappings; write model cards & uncertainty notes.
• Serve outputs via lightweight APIs/WebSockets; optimize for low latency and low power; maintain reproducibility (DVC/CI).
• Collaborate across disciplines to translate model signals into human-centered interaction and clear narratives.
You’re a fit if you have
• Strong Python + ML (PyTorch/Lightning or JAX; scikit-learn) and time-series/geospatial skills (xarray, rasterio, geopandas).
• Data engineering/MLOps hygiene (Pydantic, DVC, Prefect/Airflow; conda/poetry, Docker, CI).
• Bonus: hydrology/remote sensing (ERA5/IMERG/GLOFAS/ICESat-2), explainability, XR data interfaces (Unity/WebSocket/HTTP).
• Interdisciplinary fluency: you communicate with scientists, artists, curators, and policymakers; you value accessibility, ethics, and inclusive design; you write crisp docs and you ship.
Why this is so special
Greenfield responsibility, real datasets, public impact. Your models power an experience people remember—and act on. Small team, high trust, creative latitude, and an open, modular platform communities can adapt with local water data.
How to apply
Email [email protected] with subject “AI Engineer — Noéa” with the following:
1. Motivation letter and a brief design plan (how you’d approach the pipeline),
2. CV / LinkedIn
Only selected candidates will be contacted.
Meeting of Waters is an equal-opportunity, access-first team. We welcome diverse backgrounds, languages, and lived experiences—especially across the Global South and riverine communities.
Key Skills
Ranked by relevance
ai
machine learning
python
docker
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- Posted
- Oct 20, 2025
- Type
- Contract
- Level
- Entry
- Location
- Geneva
- Company
- Meeting of Waters
Industries
Performing Arts
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
View Job Details
Related
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2026-05-20
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View Job Details
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