Job Opportunities API

THE COMPANY We are NEURAL EARTH. We bring clarity to physical risk, enabling leaders to engage with confidence and enact resilient, business-critical decisions. Today's environmental, economic, and infrastructure challenges are deeply interconnected, yet the data required to understand these relationships is scattered across siloed and aging systems. Neural Earth enables operational execution, delivering a single decision intelligence platform that unifies planetary, governmental, and asset-level data, always on and always learning. This is technical work that requires patience. It requires teams willing to operate at the intersection of AI research, geospatial science, distributed systems, and enterprise deployment. It is also incredibly rewarding. Join us at Neural Earth — the next frontier is here. THE TEAM Neural Earth's Science team transforms raw environmental data into intelligence that moves markets and protects lives. You will join a growing group of atmospheric scientists, ML specialists, and geospatial researchers led by a strong leader, who sets a high bar: the work must be publishable in quality and deployable in production. You will collaborate closely with Engineering, Product, and Revenue to make sure what we build in science reaches the customers who need it. THE ROLE This is a founding role. You will own Neural Earth's weather and atmospheric analytics function, define the science strategy, and translate multi-hazard data into quantified intelligence products used by insurers, government agencies, and infrastructure operators. You work at the intersection of atmospheric science, machine learning, and geospatial engineering. You do not stop at the paper. You build things that ship, scale, and make hazard data understandable to people who are not scientists. This is you! HOW YOU'LL BE SUCCESSFUL - Model: Design and deploy Python-based numerical weather prediction and geospatial models that quantify atmospheric hazards at a level of precision that drives real business decisions, not just research outputs. - Build: Architect Neural Earth's atmospheric analytics capability from the ground up, including the team, data pipelines, and scientific frameworks that turn hazard data into indexed intelligence products customers can act on. - Translate: Convert complex, multi-hazard scientific findings into business-ready products that are legible and compelling to insurance underwriters, government operators, and enterprise decision-makers. - Lead: Serve as Neural Earth's internal and external subject matter expert on weather and climate, driving customer calls, proposals, and strategy discussions. - Validate: Establish rigorous validation standards for all atmospheric models, ensuring methods are reproducible, cross-validated, and defensible across industries and geographies. WHY WE VALUE YOU - You have 3 or more years working with atmospheric and geospatial data, including numerical weather prediction models (WRF, ECMWF) and multi-hazard analysis at scale. - You write Python fluently and have built production-grade geospatial models using GeoPandas, Rasterio, GDAL, xarray, and Shapely. - You have applied ML to real atmospheric or climate problems using PyTorch, TensorFlow, or scikit-learn and shipped the results. - You are fluent in geospatial data formats (GeoTIFF, COG, GeoParquet, NetCDF) and have worked with large-scale raster, vector, and time-series datasets in cloud environments. - You have shaped a scientific framework or research agenda, not just executed within someone else's. - You think in systems. When you see a wildfire burn scar, your mind goes to downstream snowpack risk. - You can walk a customer through a confidence interval in the morning and brief a C-suite on business implications in the afternoon. - You define your own structure in ambiguous environments and build something real before the roadmap is written. - You do not ship unvalidated models. You have t