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HomeCompaniesPear VCStructural & Disaster Exposure Engineer - ResiQuant

Structural & Disaster Exposure Engineer - ResiQuant

Pear VC · San Francisco · On Site · Active · Ashby

Job facts

FieldValue
CompanyPear VC
TitleStructural & Disaster Exposure Engineer - ResiQuant
Normalized title-
Department / teamResiquant / Resiquant
LocationSan Francisco, CA, United States
Work modelOn Site
Employment typeFull Time
Salary-
Statusactive
ATS providerAshby
Posted / first seen / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Pear VC.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Ashby.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Resiquant.Open
Work model jobsActive On Site postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyPear VC
Source80a05232-19b7-4cc5-bbca-3236f88fbe9d
ATS providerAshby

Description

About Us: 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. The Role 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. What You'll Do Analyze building imagery and varied property documents to create comprehensive datasets that teach AI systems how expert engineers assess structures across different US regions and construction practices. Collaborate directly with AI and backend engineering teams to implement your structural expertise in our product to ensure accuracy at scale. Support customer success by interacting with insurance customers and handling domain-specific technical questions. Define failure modes and vulnerability frameworks for buildings subjected to earthquakes, hurricanes, wildfires, and other natural hazards. Review and validate AI-generated structural assessments to continuously improve model accuracy. Who You Are 2–6 years of structural engineering consulting experience with existing buildings (retrofit design or forensic investigations preferred). BS in Civil/Structural Engineering required. Master's in Structural Engineering preferred. Deep knowledge of US building codes, permits, and regional construction practices. Technical understanding of building failure modes during disasters. AI mindset: excited by AI developments and eager to combine them with structural engineering expertise. Thrive in fast-paced, high-ownership environments with a founder mentality. Excited to relocate to San Francisco and commit to 5-days in-office collaboration. Nice to Have Catastrophe modeling experience (hurricane, earthquake, severe convective storm, wildfire). Functional programming skills in Python. Statistics and probability knowledge. Why Join Us Founding Impact: Be a founding engineer shaping how AI transforms risk assessment in the $200B property insurance industry. Growth: Work directly with Stanford PhD founders and AI researchers; accelerate your technical and leadership trajectory. Innovation: Build at the frontier of AI, structural engineering, climate science, and catastrophe modeling. Mission: Protect communities and businesses from disaster impacts. What We Offer Competitive salary + significant equity. Full medical, dental, and vision benefits. 401(k) with company match. Daily lunch + commute support in our SF office. Fast-paced, mission-driven environment with access to cutting-edge AI and research.

Full job record

Job ID7991268e512b2eef1c2c94f3ed0d1028c1a8b552
Org IDf6e6cb7d-00d2-42f1-bc64-0a9f21fd5ab6
Source ID80a05232-19b7-4cc5-bbca-3236f88fbe9d
Board ID80a05232-19b7-4cc5-bbca-3236f88fbe9d
Providerashby
Provider Job Keyf030e8fe-0e6b-436e-bd5c-3799e8b6d5f5
TitleStructural & Disaster Exposure Engineer - ResiQuant
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco
DepartmentResiquant
TeamResiquant
Employment Typefull_time
Workplace Typeon_site
Remote Policy
CountryUnited States
RegionCA
CitySan Francisco
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://jobs.ashbyhq.com/Pear-VC/f030e8fe-0e6b-436e-bd5c-3799e8b6d5f5
Apply URLhttps://jobs.ashbyhq.com/Pear-VC/f030e8fe-0e6b-436e-bd5c-3799e8b6d5f5/application
First Seen At2026-05-29 06:16:18Z
Last Seen At2026-06-06 09:18:22Z
Last Checked At2026-06-06 09:18:22Z
Last Changed At2026-05-29 06:16:18Z
Inactive At
Source Posted At
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=Pear-VC/date=2026-06-06/2026-06-06T09-17-25-570Z-e846d15f67424e12fab46f1ce54f9f0807a744d1058805eab2e6cd8e91768b2e.json
Event Fields
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}
Parsed Structured
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}
Extensions
{}
Native Structured
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  "workplaceType": "OnSite",
  "employmentType": "FullTime",
  "secondaryLocations": []
}
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