At ResiQuant, we're tackling one of the biggest challenges in disaster resilience: the lack of accurate, standardized, and dynamic property data. In a world increasingly impacted by climate change and natural disasters like earthquakes, hurricanes, and wildfires, decisions about risk are often made with incomplete or incorrect information. Our mission is to empower insurers, financial institutions, and asset managers with AI systems fused with structural engineering expertise. These systems bridge critical data gaps to deliver precise, actionable building insights for better decision-making. Founded by Stanford PhDs, we are committed to leveraging cutting-edge AI to protect communities and businesses from disaster impacts. At ResiQuant, we're building a future where every organization has access to world-class property risk intelligence to drive resilience and safeguard what matters most. You'll expand the structural engineering intelligence that powers AI systems capable of assessing building vulnerability like expert engineers. You will generate ground truth data and define the logical reasoning frameworks that determine how buildings survive natural disasters. Working directly with our Stanford PhD founders and top-tier AI team, you'll create the technical foundation that enables insurers to make billion-dollar risk decisions with unprecedented accuracy, while positioning yourself to lead all engineering and catastrophe modeling expertise as we scale across the US and internationally.