Senior Machine Learning Engineer (Research Scientist, Fraud)

Join Plaid's Fraud Data team as a Senior Machine Learning Engineer (Research Scientist, Fraud). In this role, you will lead applied research to develop next-generation fraud detection models, design rigorous experiments, and translate promising research into production-ready solutions. You will collaborate with a highly skilled, cross-functional team and leverage Plaid's network-level financial data to uncover insights and develop solutions that help consumers achieve greater financial freedom.

Lead applied research to develop next-generation fraud detection models across various data types.

About Plaid

We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!

Responsibilities

• Design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics.
• Translate promising research into production-ready solutions and communicate findings to advance the technical bar for fraud machine learning.

Requirements

• 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
• PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a closely related field strongly preferred. Candidates without a PhD may be considered with equivalent research experience, such as significant publications, patents, or widely adopted research contributions in relevant fields
• 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 business impact
• Experience in fraud detection, security, risk, or abuse prevention
• Experience with large-scale training, graph systems, and sequential modeling

Pay

USD 228,960 - 315,360