Machine Learning Engineer

About the role

At Stand, you will contribute to the development of innovative global property protection solutions. Utilizing advanced physics and artificial intelligence, we create models that assess catastrophic risks at the asset level, enabling proactive underwriting and risk mitigation. Our primary product is the Stand World Model, a scalable risk engine that transforms the insurance landscape.

Key facts

What you'll do

• Create, implement, and deploy machine learning systems that incorporate multimodal learning, physics-informed AI, digital twins, and spatial intelligence, directly impacting our core business.
• Manage projects from start to finish, including defining problems, prototyping, deploying solutions, and monitoring performance post-launch.
• Establish comprehensive evaluation frameworks to assess model predictions against actual business results.
• Enhance and expand our scalable machine learning infrastructure.
• Collaborate with the Platform team to integrate models into existing workflows.
• Foster cross-functional collaboration by effectively communicating decisions, trade-offs, and project updates.

Requirements

• Extensive hands-on experience in designing and training multimodal models that integrate diverse data types, such as 3D/vision, simulation outputs, tabular data, and text.
• Proven track record of deploying models in production, including training, evaluation, and ongoing improvements in live environments.
• Experience applying machine learning to intricate physical systems, regardless of the specific domain (e.g., atmospheric, molecular, robotics, etc.).
• Familiarity with training or fine-tuning large language models, including their application in agentic workflows or post-training techniques.
• Strong project management skills, including the ability to plan, prioritize, and execute complex technical initiatives.
• Capability to bridge technical development with business goals across various disciplines.
• Excellent communication skills and sound judgment to balance research and development with delivery timelines and business objectives.
• Highly self-driven, adaptable, and comfortable working in fast-paced, uncertain environments.

Nice to have

• Experience with retrieval and embedding systems, particularly in vector search and similarity in latent spaces.
• Background in geometric deep learning, including point clouds, meshes, and spatially-aware architectures.
• Knowledge of physics-informed AI and surrogate modeling across various fields.
• Experience in startup environments or in developing new technologies from the ground up.
• Familiarity with geospatial, remote sensing, or Earth observation datasets.

Compensation

The annual salary for this position ranges from $250,000 to $295,000, along with a significant equity grant.

Compensation decisions are influenced by factors such as individual qualifications, job location, internal equity, and market standards.

Benefits

• Comprehensive Health, Dental, and Vision insurance
• Weekly lunch stipend
• Flexible time off plus holidays
• 401(k) retirement plan
• Commuter benefits
• Paid parental leave
• Short-Term and Long-Term Disability coverage
• Monthly team events
• In-office perks

Work Authorization

Candidates must have authorization to work in the United States. Stand does not provide sponsorship for new work visas. We can consider candidates on TN, O-1A, or H-1B visas with at least three years remaining.

Equal Opportunity Employment

Stand is committed to equal opportunity and does not discriminate based on veteran status, disability, or other legally protected statuses. We value diversity and aim to build a team that reflects a variety of backgrounds and experiences.

We are dedicated to providing reasonable accommodations for qualified individuals. If you need assistance, please let us know.

In accordance with the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.