Microsoft's AI for Earth is looking for a Principal Geospatial Infrastructure Engineer, who will play a role in accelerating the impact of this program via a “Planetary Computer”: a set of geospatial data and distributed computing tools that enable global-scale analyses for conservation and sustainability.
In this role, you will lead the design and implementation of architectures for distributed geospatial data processing, from rapid prototyping to production development. Applicants should have a background in software engineering, geography/GIS, or related fields, and be fluent with GIS software and Python.
Principal Geospatial Infrastructure Engineer, AI for Earth - Sustainability
Microsoft’s AI for Earth program accelerates innovation at the intersection of machine learning and environmental science, through grants, data hosting, and technology development. We build machine learning and cloud computing tools that advance the state of the art in conservation technology, and we work directly with grantees, customers, and partners to apply those tools to real-world problems. The next milestone for the AI for Earth program is to accelerate the impact of this work via a “Planetary Computer”: a set of geospatial data and distributed computing tools that enable global-scale analyses for conservation and sustainability.
This role will lead the design and implementation of architectures for distributed geospatial data processing, from rapid prototyping to production development. The core of the work will focus on creating a development environment for Earth science practitioners to leverage geospatial data on Azure, building on both OSS and commercial tools.
- Design and implement architectures for distributed geospatial processing
- Design and implement data processing and ingestion pipelines
- Prepare tutorials and educational examples to facilitate on-boarding of new Planetary Computer users
- Work with external collaborators to deploy this architecture into applications in conservation and sustainability
- Work with our data science team to facilitate the development of machine learning tools and applications on top of the core geospatial infrastructure
- Fluency with Python required
- Fluency with open-source, cloud-based geospatial analysis tools (e.g. Pangeo, STAC) required
- Fluency with geospatial raster analysis tools (e.g. rasterio, GDAL) required
- Fluency with GIS software (e.g. ArcGIS, QGIS, CARTO, Mapbox) required
- Fluency with Linux required
- Fluency with cloud (Azure, AWS, or GCP) infrastructure required
- Fluency with one or more cloud-based distributed computing/querying frameworks (e.g. Kubernetes, Hadoop, Spark, Dask, Azure Batch, BigQuery) required
- Experience with Jupyter required, experience with JupyterHub and/or BinderHub strongly preferred
- Fluency with collaborative platforms (e.g. GitHub, GitLab) required
- Masters or PhD in computer science, software engineering, remote sensing, geography/GIS, or related fields required
- At least seven years of experience working in software engineering and/or software architecture required
Familiarity with machine learning preferred, but not required
Interest and comfort in engaging with the environmental science and sustainability communities preferred, but not required
- Familiarity with R preferred, but not required
The team is in Redmond, Washington; candidates able to relocate to the Puget Sound area are preferred, but remote candidates will be considered.
Visit Microsoft's career opportunities page here to view full job details and to begin your application.
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