Machine Learning Engineer – Multimodal Modeling

Stand

Machine Learning Engineer designing and deploying AI capabilities for the multimodal Stand World Model. Collaborating with teams to enhance underwriting and pricing decisions.

Posted 7/19/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $250,000 - $295,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying machine learning systems, particularly in multimodal learning and physics-informed AI, while effectively aligning technical development with business objectives. Proven ability to manage projects end-to-end, ensuring rigorous evaluation and performance monitoring of models in production.

Highest-signal resume keywords

Multimodal Model DesignProduction Deployment of ML ModelsTraining and Fine-Tuning LLMsProject Ownership and ExecutionCross-Functional Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModel Evaluation FrameworksScalable ML InfrastructureData Fusion TechniquesComplex Physical Systems ModelingTraining at ScaleAgentic WorkflowsPost-Training MethodsPrototypingPerformance Monitoring

Soft Skills

Strong CommunicationJudgmentSelf-MotivationProactivityAdaptability

Industry Keywords

Digital TwinsSpatial IntelligencePhysics-Informed AI3D/Vision DataRoboticsFluid DynamicsAtmospheric ModelingMolecular ModelingProtein ModelingHeterogeneous Data

About the role

Key responsibilities & impact

Design, build, and deploy machine learning systems spanning multimodal learning, physics-informed AI, digital twins, and spatial intelligence, contributing directly to core business impact
Own projects end-to-end, from problem definition and prototyping through production deployment, adoption, and ongoing performance monitoring
Develop rigorous evaluation frameworks that weigh model judgments against real business outcomes
Build on and extend scalable ML infrastructure
Partner with Stand’s Platform team on the model-harness interface
Drive cross-functional alignment, communicating decisions, tradeoffs, and status

Requirements

What you’ll need

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. We are agnostic to the domain: atmospheric, molecular, protein, robotics, fluid dynamics, or other physics-grounded modeling all carries over
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

Comp & perks

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