Top AI & Machine Learning Jobs in San Francisco, CA

The Senior Staff Data Scientist leads data-driven insights for product development and strategy in the investment sector, collaborating with cross-functional teams and optimizing portfolio performance.

The Staff AI Engineer will architect and develop AI systems for risk management, focusing on usability, reliability, and scalability, while collaborating cross-functionally to implement innovative solutions.

The role involves building and scaling machine learning models to drive marketing performance at SoFi, focusing on customer acquisition, retention, and LTV using data analysis and modeling.

Drive the design and development of AI and ML solutions for member growth, leading technical architecture and mentoring engineers while focusing on advanced personalization and collaboration across teams.

As a Senior Staff Data Scientist, you'll leverage data analysis and ML models to support SoFi's Home Loans growth. This includes high-level technical leadership, mentoring, stakeholder communication, and building data pipelines.

Lead the Modeling and AI Enablement function within Marketing Data Science, guiding AI strategies, model development, and governance while managing a team of data scientists.

The Senior Data Scientist will develop and validate AML models, oversee implementation, ensure compliance with regulations, and collaborate with governance units.

Lead the development and implementation of AI agents for financial guidance. Define technical strategies, mentor engineers, and ensure compliance with industry standards.

As Director, AI Platforms, you will lead the development of AI-enabling platform services, ensuring compliance, reliability, and adoption across teams. You will manage multi-tenant services and drive AI integration into the SDLC, shaping strategies and overseeing platform governance.

The Credit Strategy Lead will analyze data to propose credit risk strategies for lending products, collaborate with teams to drive revenue, and develop innovative risk management approaches.