Job Description
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real world production systems. As a Machine Learning Engineer on the Embedded Insights team, you will drive machine learning initiatives from concept to production, working across the full model development lifecycle. You will leverage Plaid’s unique datasets to identify high-impact opportunities for machine learning, develop proofs of concept to validate new approaches, and build MVP solutions that demonstrate customer value. Partnering closely with product managers, engineers, and other cross-functional stakeholders, you will embed within product teams to translate successful prototypes into scalable, customer-facing products. As solutions gain traction, you will help expand their reach by optimizing models for new use cases, improving system scalability, and incorporating customer feedback gathered before and after launch. You will also be responsible for maintaining and enhancing existing machine learning systems throug
