Who we are 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, 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 team

Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using 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. You can learn more about our team’s work from this recent talk.

What you’ll do

As a staff engineer you will be responsible for

Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals. Designing, training, improving & launching models  Proposing and implementing ideas Leading partner teams to launch new products Debugging production issues across services and multiple levels of the stack. Be an integral part of a larger ML community internally & externally Responsibilities

Our team operates fluidly and here are some problems you may tackle:

What product strategy should we pursue? How do we evaluate a system offline & online? How do we improve performance to match (and beat) humans? How do we ensure model quality doesn’t degrade online? Does fine-tuning an LLM give us better performance? What are the right OSS and in-house platforms we should invest in? Who you are

We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying 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 6 years of industry experience shipping ML models to production Hold yourself and others to a high bar when working with production systems Take pride in taking ownership and driving projects to business impact Thrive in a collaborative environment Preferred qualifications 10+ years of experience in full time software development roles Experience shipping LLM integrations to user products with high quality Experience operating in highly ambiguous environments Knowledge about driving a hypothesis from data