Job Overview
Location
San Francisco
Job Type
Full-time
Category
Machine Learning Engineer
Date Posted
July 21, 2026
Full Job Description
đź“‹ Description
- • 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 designing and training multimodal model architectures that jointly reason over physical, spatial, and business-context data, building frameworks that let these models act as agents within nuanced workflows, making complex tool calls that include interacting with our world-modeling stack, developing retrieval and similarity capabilities over learned representations of real-world assets and their multi-layered complexities, and standing up the training-data pipelines, evaluation harnesses, and production monitoring that take these models from prototype to production.
- • You will design, build, and deploy machine learning systems spanning multimodal learning, physics-informed AI, digital twins, and spatial intelligence, contributing directly to core business impact.
- • You will own projects end-to-end, from problem definition and prototyping through production deployment, adoption, and ongoing performance monitoring.
- • You will develop rigorous evaluation frameworks that weigh model judgments against real business outcomes.
- • You will build on and extend scalable ML infrastructure.
- • You will partner with Stand’s Platform team on the model-harness interface.
- • You will drive cross-functional alignment, communicating decisions, tradeoffs, and status.
🎯 Requirements
- • Deep hands-on experience designing and training multimodal models, fusing heterogeneous data (e.g., 3D/vision, simulation outputs, tabular, and text) into shared representations.
- • A record of bringing models of this class to production: training at scale, evaluation, deployment, and iteration on live systems.
- • Experience applying ML to complex physical systems.
- • Experience training or fine-tuning LLMs, including tool use, agentic workflows, or post-training methods.
- • Strong project ownership and execution: planning, prioritization, and delivery of complex technical work.
- • Ability to operate across disciplines, connecting technical development to business objectives.
- • Strong, succinct communication and judgment to balance R&D, delivery timelines, and business impact.
- • Highly self-motivated, proactive, and adaptable; comfortable in fast-paced, ambiguous environments.
🏖️ 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
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
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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