Zipline

Dear Zipline,

I’m applying for the Spatial Planning Intern (Summer 2026) role. I’m an EECS student at UC Berkeley with strong Python and C++ skills and experience building geospatial data pipelines and shipping outputs that downstream systems can directly consume.

My primary relevant project is an end-to-end satellite imagery pipeline for settlement (“Boma”) identification and spatial prioritization. I assembled and labeled a dataset of 10,000+ satellite image tiles, trained and validated a classification/detection model, and built a repeatable workflow to generate spatial artifacts (settlement locations/density surfaces) used for on-the-ground planning. I used Google Earth Engine for data generation and transformation, and Python tooling for model fitting, evaluation, and post-processing into map-ready outputs.

This maps in your team’s work on artifact generation, spatial data transforms, and routing constraints: (1) produce reliable, versioned spatial outputs, (2) validate them for quality/compliance, and (3) make them accessible for fast lookup/use by planning systems. I’m comfortable with Docker/Linux environments, modular code, and automated testing practices.

I’d like to discuss ways I can add value to Zipline’s spatial data ingestion/geoindexing and planning artifact pipeline this summer.

Sincerely,

Roshan Taneja