Top AI & Machine Learning Jobs in San Francisco, CA

Lead product strategy and delivery for Kai, Airwallex's AI assistant. Partner with engineering, design, and cross-functional teams to build scalable LLM-powered features, validate new agentic use cases, balance model quality and cost, and drive product performance using user feedback and production conversation data.

Lead development of a 0→1 agentic AI finance product: define strategy, design solutions and UX, collaborate with engineering, design, and commercial teams, achieve product-market fit, and scale using cutting-edge LLM techniques.

Lead strategy, roadmap, and execution for AI-powered fintech products. Build and ship LLM/ML-driven features (copilots, chatbots, recommendation systems), drive PLG and automation, ensure responsible AI and compliance, launch globally across regions/languages, and mentor other product managers.

Lead GTM-focused data science initiatives: build revenue forecasts, apply causal inference, develop AI-enabled sales and retention solutions, partner with Product/Growth/Commercial teams, and translate analyses into scalable, automated workflows and executive-ready recommendations.

Lead GTM data science initiatives to build revenue forecasting, causal inference analyses, and AI-enabled solutions that improve sales, retention, and expansion. Partner with Product, Growth, and Commercial teams to operationalize insights, communicate findings to stakeholders, and mentor junior data scientists.

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.

Partner with Growth, Marketing, Sales, and Product to measure and optimize marketing and growth initiatives. Build dashboards and scalable measurement frameworks, design experiments, analyze ROI and trends, provide actionable recommendations, and communicate results to technical and non-technical stakeholders.

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.

Design, build, and deploy end-to-end machine learning solutions for payment risk and fraud. Responsibilities include data and feature engineering, model training, production deployment, platform/tool development, cross-functional collaboration, and ongoing analysis to mitigate fraud and deliver business impact.

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.