Senior Machine Learning Engineer (Research Scientist) - Fraud

The role

You will lead applied research to develop next-generation fraud detection models using relational graphs, sequential events, images, and video data. You will partner with Machine Learning Engineers to translate research into production-ready solutions.

What you will do

• Research and prototype state-of-the-art approaches across graph machine learning, sequential modeling, and multimodal learning.
• Own and execute a research roadmap that translates innovative ideas and prototypes into production solutions.
• Publish and share applied research while collaborating with cross-functional teams.
• Leverage Plaid’s network-level financial data to uncover insights and develop solutions.

Required qualifications

• 2–4+ years of relevant industry or research lab experience, ideally post-PhD, with demonstrated research leadership and a track record of translating innovative research into measurable product or bus
• Demonstrated scientific rigor, with strong written and verbal communication skills and the ability to clearly communicate complex research findings.
• Strong proficiency in Python and experience building high-quality research prototypes that can inform or transition into production systems.

Nice to have

• PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a closely related field strongly preferred.
• Experience in fraud detection, security, risk, or abuse prevention.
• Experience with large-scale training, graph systems, and sequential modeling.

Benefits

• Medical
• Dental
• Vision
• 401(k)

About the company

Plaid powers the tools millions of people rely on to live a healthier financial life. The company's network covers 12,000 financial institutions across the US, Canada, UK and Europe.