Machine Learning Engineer - Data Foundation and AI

Plaid•New York, NY

About The Position

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 Data Foundation & AI team builds advanced ML/AI models and applications that enable product teams to deliver intelligence at scale. We design infrastructure and abstractions that make AI development faster, more reliable, and more impactful. From embeddings and representation learning to applied AI systems, our work provides the building blocks for the next generation of financial services on Plaid. You’ll be a machine learning engineer on the Data Foundation & AI team. In this role, you will design, build, and scale advanced ML/AI systems that power Plaid products and applications. Your work may span developing reliable distributed training and serving systems, improving ML operations at scale, and building AI-powered applications that enable new product experiences.

Requirements

1-3 years of experience training, deploying, and scaling ML/AI models in production environments.
Strong experience with distributed systems and ML operations — from large-scale training to low-latency serving and monitoring.
Proficiency in Python and modern ML frameworks (e.g., PyTorch), with the ability to implement and optimize complex models.
Hands-on experience building or scaling ML/AI infrastructure, pipelines, or reusable platforms that support multiple teams.
Curiosity and drive to experiment with advanced AI techniques (e.g., embeddings, retrieval, generative modeling) while staying grounded in production impact.
Ability to thrive in a collaborative environment, working with both technical and non-technical partners to drive measurable outcomes.

Nice To Haves

Experience applying ML/AI in fintech or similarly regulated industries is a plus.

Responsibilities

Building and scaling advanced ML/AI systems that power core Plaid products and applications used by millions of consumers.
Driving impact at scale by improving distributed training, serving, and ML operations to make Plaid’s AI capabilities faster, more reliable, and more widely available.
Developing new AI applications that enable innovative product experiences across fintech.
Tackling 0 to 1 problems where you explore new approaches, as well as scaling 1 to 10 systems for reliability and efficiency.
Collaborating with some of the strongest MLEs at Plaid in a high-ownership, bottom-up driven team.
Experimenting with cutting-edge ML and AI techniques while balancing practical productionization and measurable business impact.