Machine Learning Engineer, Stripe Assistant
About the role
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet.
About the Team
The Stripe Assistant team is transforming how users interact with Stripe by building an intelligent and proactive assistant that not only answers users' queries but efficiently resolves issues and provides valuable business insights. We leverage LLMs and agentic systems to elevate the user experience across Stripe—from the dashboard to support surfaces—and we enable other teams to build and integrate their AI agents on our platform.
What You'll Do
As a Senior Machine Learning Engineer on the Stripe Assistant team, you'll own the end-to-end ML and agent architecture that makes Stripe Assistant safe, reliable, and deeply useful. You'll set the strategy for how the Assistant executes high-trust actions, delivers accurate analytical answers across Stripe and the broader web, orchestrates capabilities across many tools and agents, and grounds responses in authoritative Stripe and user data.
You'll drive conversation continuity and personalization across surfaces, evolve the Assistant into a proactive partner that anticipates user needs, and deepen its presence in the dashboard to streamline critical workflows. You'll establish rigorous evaluation and SLOs and deliver step-change improvements in quality, latency, cost, and availability.
Responsibilities
- Establish trustworthy, human-in-the-loop execution for high-trust write actions—prioritizing user control, transparency, accountability, and auditability
- Define and evolve the Assistant's capability and governance model across hundreds of tools and agents, balancing power, permissions, and consistency at scale
- Raise answer quality and usefulness by grounding in authoritative Stripe knowledge and live user data, building cross-surface memory and personalization
- Explore and apply optimal machine learning techniques to enhance Assistant performance