Job Overview
Location
San Francisco
Job Type
Full-time
Category
Data Science
Date Posted
June 4, 2026
Full Job Description
đź“‹ Description
- • Lead the Machine Learning Engineering sub-team in developing and deploying Stand’s flagship AI capabilities, including physics-informed machine learning, digital twins, computer vision, and spatial intelligence.
- • Own the technical direction, planning, and execution of critical AI initiatives, ensuring alignment with business priorities, on-time delivery, and measurable impact.
- • Directly contribute to core ML systems by designing, building, and deploying production-ready models that accelerate risk analytics, underwriting, pricing, mitigation, and customer decision-making.
- • Manage and grow the MLE team through 1:1s, performance feedback, mentoring, and career development conversations as the team scales.
- • Drive end-to-end ownership of projects from problem definition and prototyping through production deployment, adoption, and ongoing performance monitoring.
- • Extend state-of-the-art surrogate architectures and physics-informed solvers to improve simulation speed and accuracy in catastrophic risk modeling.
- • Build and improve scalable ML infrastructure including data pipelines, training systems, evaluation frameworks, and production monitoring tools.
- • Establish and refine team processes to enhance traceability, efficiency, and cross-functional coordination across Applied Science and business units.
- • Translate business needs into technical roadmaps, turning abstract requirements into concrete team deliverables that influence underwriting and risk mitigation.
- • Communicate modeling decisions, tradeoffs, and project status clearly to technical and non-technical stakeholders across the organization.
- • Set a multi-year vision for the MLE team’s impact, articulating how its work directly advances Stand’s mission to model risk at the asset level and automate insurance outcomes.
- • Partner with research teams to transition emerging technologies into scalable, production-grade systems that operate in real-world insurance workflows.
- • Maintain deep technical involvement in core AI systems while simultaneously leading team execution, prioritization, and resource allocation.
- • Ensure all AI systems are built with rigorous validation, operational reliability, and clear links to business outcomes such as reduced loss ratios and improved underwriting precision.
- • Collaborate across disciplines to integrate geospatial data, remote sensing inputs, and sensor fusion techniques into AI-driven risk models.
- • Champion process improvements that balance research depth with delivery timelines in a fast-paced, ambiguous startup environment.
🎯 Requirements
- • Proficiency with modern ML tooling and infrastructure
- • Experience leading engineers and technical initiatives, delivering complex projects through others as well as through direct individual contribution
- • Strong project ownership and execution: planning, prioritization, stakeholder coordination, and delivery of complex technical programs from concept through production
- • Experience combining physics-based modeling and machine learning, including simulation, scientific computing, surrogate modeling, and/or physics-informed AI approaches
- • Ability to operate across disciplines, connecting technical development to business objectives and customer impact, and articulating those links to the team
- • Strong, succinct communication and the judgment to balance research depth, delivery timelines, and business impact
🏖️ Benefits
- • Above-market Health, Dental, and Vision coverage
- • Weekly lunch stipend
- • Flexible time off + holidays
- • 401(k) plan
- • Commuter benefits
- • PAT & MAT Leave
- • Short-Term and Long-Term Disability
- • Monthly team gatherings
- • In-office perks
Skills & Technologies
About Stand Insurance Company
Stand Insurance Company is a digital-first insurer offering personal and small-business coverage. Its mobile app enables on-demand policies, instant claims, and flexible billing. Lines include renters, pet, event, and professional liability insurance, underwritten by admitted carriers. Data-driven pricing and AI chat support target millennials and freelancers seeking transparent, low-friction protection. Based in San Francisco and licensed in 50 states, the carrier operates on a managing general agency model, partnering with regulated reinsurers to maintain statutory capital. Founded in 2018, it has raised Series B funding and maintains an A.M. Best outlook of stable.
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