Top Fintech Machine Learning Engineer Jobs in San Francisco, CA

The Staff ML Engineer will architect, design, and develop software applications while ensuring the implementation of business requirements and technical documentation. They will collaborate with teams for project delivery, production support, and enhancements.

Design and implement AI-powered solutions for document extraction and financial reasoning, focusing on ML pipelines and application of LLMs.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

Lead a team to develop machine learning models for credit strategies, collaborating across functions and delivering measurable business outcomes.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.

As an Applied AI Engineer, you will design and implement ML systems for customer interactions, focusing on performance and scalability.

Design, develop, and deploy production machine learning models to improve decisioning for consumer lending. Partner with business and technical teams to develop data sources, improve modeling methodology, manage models in production, and mentor others while practicing strong software engineering and MLOps practices.

The Senior Machine Learning Engineer will build and operate ML systems end-to-end, focusing on production-grade ML platforms, feature pipelines, and MLOps practices while collaborating with cross-functional teams.