Plaid
Senior Machine Learning Engineer (Research Scientist) - Fraud
$229K–$315K
New York City Office +2 · Hybrid · Senior · Full-time · Posted Sep 12, 2026
- Location
- New York City Office
Seattle Office
San Francisco HQ - Experience
- 2–4+ years of relevant industry or research lab experience, ideally post-PhD; candidates without a PhD may be considered with equivalent research experience, such as significant publications, patents, or widely adopted research contributions.
- Education
- PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a closely related field strongly preferred; equivalent research experience may be considered.
About the job
Leads applied research and develops production-ready machine learning models to detect fraud using network, graph, sequential, image, and video data.
What you'll do
- Research and prototype approaches in graph machine learning, sequential modeling, and multimodal learning for fraud detection.
- Own a research roadmap and translate prototypes into production solutions with measurable impact.
- Design rigorous experiments, publish and communicate findings, and collaborate across Data, Product, and Engineering.
What they ask for
- Strong proficiency in Python and experience building research prototypes that can inform or transition into production.
- Demonstrated scientific rigor and strong written and verbal communication skills.
- Research leadership and a record of translating research into measurable product or business impact.
Nice to have
- Experience in fraud detection, security, risk, or abuse prevention.
- Experience with large-scale training, graph systems, and sequential modeling.
Pay
$228,960 – $315,360 (base salary; currency not stated)
Tools
Python, Graph Neural Networks, Transformer-based foundation models
AI focus
Applied research into next-generation fraud detection models, including graph machine learning, sequential modeling, and multimodal learning across relational graphs, sequential events, images, and video.
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