Neural Earth

You will embed within carrier or reinsurer teams to analyze exposure, diagnose loss ratio divergences, and provide actionable technical insights. Additionally, you will act as a key commercial authority, shaping the product roadmap and driving market adoption through expert-level technical arguments.

You will own the geospatial data science function by designing Python-based models and architecting robust data pipelines to transform raw environmental data into actionable intelligence. Additionally, you will lead technical strategy, mentor team members, and translate complex scientific findings into business-ready products for enterprise stakeholders.

The DevOps Lead will maintain CI/CD pipelines and containerized infrastructure while ensuring the reliability of cloud environments. They will also support incident response and perform steady-state maintenance to enable the engineering team to scale efficiently.

Design and deploy end-to-end multimodal geospatial AI models and scalable ML infrastructure. Provide technical leadership and mentorship to the team while translating product vision into technical roadmaps.

Lead the end-to-end design of a geospatial intelligence platform, focusing on map-based risk dashboards and AI-assisted workflows. Collaborate with engineering and data science teams to translate complex spatial data into intuitive interfaces for non-technical users.

This is an open submission for various roles across Product Engineering, Data Science, Revenue, and G&A. Candidates will contribute to a decision intelligence platform that unifies planetary, governmental, and asset-level data.