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, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the teamThe newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production.
What you’ll doResponsibilities- Driving an ambitious vision for AI/ML that benefits our users
- Setting the technical & process direction for the team based on business goals
- Brainstorm and coordinate product integrations with partner teams
- Proposing new ideas and building prototypes
- Be an integral part of a larger ML community internally & externally
- Hire & develop a world-class team to deliver high-quality ML systems.
- Coach engineers to help them grow in their careers and maintain a high bar
We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action.
Minimum requirements- Have at least 4 years of experience managing ML teams
- Experience working as a Machine Learning Engineer, Applied Scientist or equivalent Individual Contributor.
- Lead by example in high-growth, high-impact, ambiguous environments
- Have experience building & shipping ML systems.
- Hold yourself and others to a high bar when working with production systems.
- Thrive in a collaborative cross-functional environment
- Experience in shipping LLM & RAG systems
