Senior Machine Learning Engineer - Fraud (Research Scientist)

Plaid

🔍 Observed

$226K - $337K USD

San Francisco First seen 2 weeks, 6 days ago Last seen 1 hour, 44 minutes ago Lever

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Job Description

AI Summary

• Lead applied research and development of fraud detection models using advanced techniques like Graph Neural Networks and Transformer-based architectures on relational, sequential, image, and video data. • Design scalable ML infrastructure and systems for fraud detection, including model deployment, monitoring, and observability frameworks that operate reliably at scale across hundreds of customers. • Mentor engineers, shape technical vision for the Fraud Data team, and publish research to advance the state of fraud ML both internally and externally. • Requires PhD (or equivalent research experience with strong publication track record), 3+ years as ML Engineer/Research Scientist, strong Python skills, and fraud/security domain expertise. • Remote-friendly position at Plaid, a fintech company processing data from 12,000+ financial institutions, with collaborative teams across ML Infrastructure, Product, and Engineering.

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***

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. Qualifications: 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. Fraud / security / abuse domain experience. - Nice to have Experience with large-scale training, graph systems, and sequential modeling. - Nice to have

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Job Information

Company:
Plaid
Location:
San Francisco
Job Type:
Full-Time
Experience Level:
Senior
Source:
Lever
Status:
Active

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65 /100

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