DevOps & Machine Learning Expert

About the role

The DevOps & Machine Learning Expert will design, implement and operate cloud‑based pipelines that deploy hydrological and climate forecasting models for IGAD’s early‑warning systems. The role supports regional flood and drought monitoring services and ensures continuous, reliable delivery of data products.

Key responsibilities

• Maintain and automate the operational hydrological forecasting chain, ensuring uninterrupted service during new product releases.
• Develop and manage multi‑cloud infrastructure as code using ecFlow, Prefect, Docker, Kubernetes and Helm.
• Implement CI/CD, GitOps (ArgoCD) and observability pipelines for production ML models.
• Provide technical support to member states and national meteorological services on flood monitoring.
• Build and maintain STAC API services, data processing workflows, and impact‑based forecast bulletins.
• Create comprehensive documentation, deployment guides, JupyterHub tutorials and training materials.

Required profile

• University degree in Computer Science, Data Science, Geo‑Informatics or related field (advanced degree advantageous).
• Minimum 4 years experience in geo‑application development, cloud operations and production ML model deployment.
• Proven ability to work with national institutions in an operational early‑warning context.
• Strong problem‑solving mindset, self‑driven and effective team collaborator.

Required skills

• Python, SQL, PostGIS, TimescaleDB.
• Web technologies: HTML, CSS, JavaScript, Node.js, React, Mapbox GL, Leaflet, GeoServer, MapServer, GDAL.
• Geospatial standards (WMS, WFS, WCS, WPS) and STAC API / PySTAC.
• Workflow tools: ecFlow, Prefect, xarray, dask, rasterio, geopandas.
• Container orchestration: Docker, Kubernetes, Helm; GitOps with ArgoCD.
• Multi‑cloud platforms: Google Cloud Platform, AWS; IaC with Terraform, Coiled.
• GPU/CUDA environment management and MLOps practices.