Machine Learning Engineer
About the Role
At Stripe in the Financial Services space, Economic infrastructure for the internet, powering ambitious businesses globally..
<h2><strong>Who we are</strong></h2>
<h3><strong>About Stripe</strong></h3>
<p>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.</p>
<h3><strong>About the team</strong></h3>
<p>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<a href="https://Stripe.com/sessions/2024/a-blueprint-for-ai-acceleration"> from this recent talk</a>.</p>
<h2><strong>What you’ll do</strong></h2>
<p>As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training &amp; evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community.</p>
<h3><strong>Responsibilities</strong></h3>
<p>Our team operates fluidly and here are some problems you may tackle:</p>
<ul>
<li>How do we evaluate a system offline &amp;
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