Hands-on role designing and training multimodal models that fuse the Stand World Model with large language models for underwriting, pricing, and mitigation decisions. The work includes building LLM agents that call tools, retrieval over learned asset representations, and training-data and evaluation pipelines. It partners with the Platform team on the model-harness interface.
Why Join Stand: At Stand, you’ll help build a new class of global property protection. We use advanced physics and AI to model catastrophic risk at the asset level, then automate underwriting and mitigation before loss occurs. Insurance is simply the current delivery mechanism. The real product is a scalable risk engine, our Stand World Model.
We stay when traditional insurers exit. We model what others approximate. And we build systems that change outcomes, not just prices.
Our leadership team has built category-defining companies (Metromile, Policygenius, WePay, HotelTonight) and brings decades of expertise in underwriting, capital management, and reinsurance.
Background: The property insurance industry is built to price loss after it happens. It relies on coarse proxies, backward-looking data, and manual processes, then accepts damage as unavoidable.
Stand takes a different approach. We simulate how real-world catastrophes affect individual properties, translate that into actionable decisions, and automate the business around it. The result is a platform that can underwrite what others can’t and operate with far less friction.
Role Summary:
As a Machine Learning Engineer on the Applied Science team, you will design, train, and deploy Stand's flagship AI capabilities, with a central focus on the multimodal meshing of our Stand World Model with powerful language models. This work brings physical simulation, rich 3D representations of real assets, and broader business context together into models that can reason across all of them at once, in support of better underwriting, pricing, and mitigation decisions.
This is a hands-on, high-ownership position on the Machine Learning team within Stand Applied Science. You will own modeling work end-to-end, from architecture and training strategy through evaluation and production deployment, and partner closely with the Platform team to ensure the agentic harness and workflows your models plug into deliver strong results in production.
Your partnerships will extend across the business, mirroring the breadth of the model's inputs: collecting technical insight from subject matter experts and other MLEs, and institutional judgment from underwriting, pricing, mitigation, inspection, and customer decision-making.
Key initiatives include:
What You'll Do:
Core Skills (Must-Haves):
Nice to Haves:
Compensation:
The annual base salary range for full-time employees in this position is $250,000 to $295,000 + meaningful Equity Grant.
Compensation decisions are dependent on several factors including, but not limited to, an individual’s qualifications, location where the role is to be performed, internal equity, and alignment with market data.
Benefits:
AI in the Interview Process
Thoughtful use of AI tools is expected and valued at Stand. Candidates should be prepared to discuss how they use AI, how they evaluate its output, and how it informs their work. Strong communication, sound judgment, and the ability to clearly articulate experience and decision-making remain core requirements.
Some parts of the interview process are designed to assess independent thinking, communication, and problem-solving. If you plan to use an AI assistant or LLM during any portion of an interview, please discuss it with your interviewer in advance.
Work Authorization
Candidates must be authorized to work in the U.S. Stand does not sponsor new work visas. We can consider candidates on TN visas, O-1A visas, or H-1B transfers with three years or more remaining.
Equal Opportunity Employment
Stand is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. We believe that diversity enriches the workplace, and we are committed to growing our team with the most talented and passionate people from every community.
We are committed to providing reasonable accommodations for qualified individuals. If you require assistance, please contact us at [email protected].
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
AI Use in Hiring
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us at [email protected].
Compensation: $250K - $295K