Senior Machine Learning Engineer - Fraud (Research Scientist)

Plaid • Washington, DC

7d • Remote

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 team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s cutting-edge fraud detection products. By leveraging Plaid’s extensive network data, we enable proactive fraud prevention—stopping fraud before it happens. Our team owns the entire ML lifecycle, from developing feature pipelines and training models to deploying and monitoring them in production. We ensure that our systems scale reliably and efficiently as Plaid continues to grow and support hundreds of customers.

As a Senior Machine Learning Engineer (Research Scientist) on Plaid’s Fraud Data team, you will design and build scalable ML infrastructure that powers our industry-leading fraud detection product. You’ll lead the evolution of our model deployment, monitoring, and observability frameworks to ensure high reliability and performance at scale. Collaborating closely with teams across ML Infrastructure, Product, and Engineering, you’ll deliver robust systems that protect users and customers from fraud. In addition, you’ll mentor other engineers and help shape the long-term technical vision and strategy of the Fraud Data team.

We are open to remote candidates for this role

Requirements

• PhD strongly preferred; we will consider equivalent research experience with a strong publication/innovation track record
• 3+ years of experience as a Machine Learning Engineer or Research Scientist
• Strong scientific rigor and communication
• Strong Python skills + ability to build high-quality research prototypes

Nice To Haves

• Fraud / security / abuse domain experience
• Experience with large-scale training, graph systems, and sequential modeling

Responsibilities

• Lead applied research to develop next-generation fraud models over relational graphs, sequential events, images, and videos data.
• Design and run rigorous experiments and develop evaluation methodologies that reflect real-world fraud dynamics.
• Prototype state-of-the-art model architectures (Graph Neural Networks, Transformer-based foundation models) and translate successful prototypes into production with fellow MLEs.
• Publish and communicate results internally and externally raising the technical bar for fraud ML at Plaid.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree