Top AI & Machine Learning Jobs in San Francisco, CA

Staff Data Scientist partnering with Growth, Marketing, Product, and Engineering teams to build data science solutions that drive customer acquisition, engagement, and retention. Responsibilities include predictive modeling, personalization, recommendation systems, LLM applications, incentive optimization, causal inference, marketing impact measurement, technical mentorship, and strategic leadership. The role requires deploying production machine learning systems and communicating analytical insights to senior stakeholders.

Leads Growth Data Science, partnering with executive, product, marketing, sales, finance, and regional teams to drive growth strategy. Oversees experimentation, causal inference, forecasting, segmentation, attribution, optimization, dashboards, and machine learning initiatives across the customer lifecycle. Establishes measurement frameworks, productionizes analytical models and intelligent tools, and manages a high-performing technical team while translating complex analyses into measurable business outcomes.

Lead strategy, roadmap, and delivery of AI/LLM-powered growth products across payments and financial operations. Own end-to-end product lifecycle, mentor product managers, build copilots/chatbots/recommendation systems, run experiments and analytics to drive PLG, and ensure responsible AI and regulatory compliance while launching products across regions and languages.

Design, build, and deploy production AI agents and orchestration systems using tools like LangChain and LlamaIndex. Apply prompting, RAG, fine-tuning, and model selection. Architect agent reasoning and workflows, implement monitoring and evaluation, and integrate AI systems with backend and frontend services for scalable, reliable, compliant production deployments.

Lead the 0→1 development of an agentic AI finance product: define strategy, design UX, prioritize roadmap, partner with engineering, design, and customers to achieve product-market fit and scale.

Design and deploy agentic AI systems that automate multi-step financial workflows. Architect agents using frameworks like LangChain and LlamaIndex, apply prompting, RAG, and fine-tuning, optimize reasoning and tool use, build feedback-driven systems, and integrate AI reasoning securely into production backend and frontend services.

Lead a zero-to-one agentic AI finance product: define strategy, design UX, iterate to product-market fit, and collaborate with engineering, design, commercial teams and customers to ship scalable AI automation across payments, payroll, bookkeeping and tax.