Machine Learning Engineer at Stripe focused on enhancing support experiences using AI. The role involves designing, building, training, evaluating, and deploying ML models, particularly LLMs, for applications like conversational agents, personalized documentation, and automated problem-solving. The engineer will work on RAG, tool use, agentic architectures, and post-training methods, collaborating with cross-functional teams to integrate AI into support systems and products.

Stripe's ML Infra team is seeking a Software Engineer to build and scale the ML lifecycle services, including training, serving, and LLM applications, to accelerate AI/ML adoption across the company. The role focuses on designing and implementing robust, high-availability infrastructure for production ML platforms.

Stripe is seeking a Machine Learning Engineer for their Supportability Evaluation team. This role focuses on designing, building, training, evaluating, and deploying AI/ML models and large-scale systems for detection and decisioning within Stripe's financial ecosystem. The engineer will work on scaling an LLM-based system, integrating new capabilities through agentic approaches or supervised learning, and ensuring merchant compliance in real-time.

Stripe is building a new team to deploy LLM agents and tools to automate engineering workflows and accelerate engineering productivity. This role will build the next generation of internal AI coding tools and platforms.

Engineering Manager for the Agent Experience team at Stripe, focusing on building infrastructure to enable AI agents to transact and scale within financial systems. The role involves leading and scaling a team of engineers, defining agentic strategy, and ensuring rapid, reliable delivery of complex back-end systems and developer tools in a regulated financial environment.