AI Urban Heat Island Mapping Engineer

Kelvix Systems

Hybrid · $160k – $200k / year · Full-time · Posted 4 months ago

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About the role

Urban heat islands kill people. In Chicago's 1995 heat wave, 739 people died — disproportionately in dense, low-income neighborhoods with little tree canopy and high impervious surface coverage. City planners and public health agencies now want to map heat vulnerability at block level and model the impact of interventions: adding tree canopy here, replacing asphalt rooftops there. We process Landsat and Sentinel-3 thermal data, LiDAR urban structure scans, and street-level imagery to build 1-meter resolution heat maps for 38 cities. The current pipeline produces accurate average temperatures. What cities want is predictive: given a planned tree-planting or cool roof program, what will the temperature change be in 2030 under a 2°C warming scenario? You'll build the predictive modeling layer: combining satellite thermal data with urban morphology features, training models on cities where we have longitudinal temperature records, and deploying the intervention simulation API that city planners use to evaluate policy options. The role is hybrid — 2 days per week in our DC office for stakeholder meetings with government clients.

Responsibilities

Build predictive urban temperature models combining thermal and morphology data at 1m resolution
Design intervention simulation: model temperature change from tree canopy and reflective surface additions
Integrate climate scenario projections into 10-year urban heat forecasts
Create model validation against historical temperature records in instrumented cities
Develop APIs for city planner intervention scenario exploration
Present modeling methodology to government clients and public health researchers

Requirements

6+ years in geospatial ML, remote sensing, or environmental data science
Experience with thermal remote sensing data and urban physics models
Strong Python and computer vision skills with satellite imagery processing
Familiarity with climate modeling and downscaling techniques
Ability to communicate technical models to non-technical government stakeholders