Plaid

Senior Machine Learning Engineer (Research Scientist) - Fraud

Plaid$150K — $180K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in Machine Learning, AI, Computer Science, Statistics, Applied Mathematics or related field preferred, with alternative experience considered.
  • 2-4+ years of relevant industry or research experience, ideally post-PhD, demonstrating research leadership and measurable impact.
  • Demonstrated scientific rigor with strong communication skills for conveying complex findings.
  • Proficient in Python with experience in building research prototypes for production.

Responsibilities

  • Research and prototype cutting-edge graph machine learning, sequential modeling, and multimodal approaches for fraud detection.
  • Own and implement a research roadmap to translate ideas into impactful production solutions.
  • Collaborate across Data, Product, and Engineering teams to publish and share applied research results.
  • Use Plaid's financial data to extract insights that empower consumers toward greater financial freedom.

Benefits

  • Comprehensive benefit plan including medical, dental, and vision coverage.
  • 401(k) retirement plan with company match.
Full Job Description
We are the Fraud Data team within Plaid's Fraud organization. We leverage relationships and activity across Plaid's network to develop machine learning models that help customers detect and prevent fraud while minimizing friction for legitimate users. Our team owns the full model lifecycle, from data processing and experimentation to feature pipelines, model serving, and monitoring. In this research role, you'll partner closely with Machine Learning Engineers and Data Scientists to uncover new signals, explore and evaluate innovative modeling approaches, and translate promising research into production-ready solutions that strengthen fraud detection across Plaid's network.

As a Senior Research Scientist, you will lead applied research to develop next-generation fraud detection models across relational graphs, sequential events, images, and video data. You'll design rigorous experiments and evaluation methodologies that reflect real-world fraud dynamics, while exploring state-of-the-art approaches such as Graph Neural Networks and Transformer-based foundation models. In close partnership with Machine Learning Engineers, you'll translate promising research into production-ready solutions and communicate your findings internally and externally to advance the technical bar for fraud machine learning at Plaid.

Responsibilities:
  • Research and prototype state-of-the-art approaches across graph machine learning, sequential modeling, and multimodal learning to build next-generation fraud detection capabilities.
  • Own and execute a research roadmap that translates innovative ideas and prototypes into production solutions with measurable product and customer impact.
  • Publish and share applied research while collaborating with a highly skilled, cross-functional team across Data, Product, and Engineering.
  • Leverage Plaid's network-level financial data to uncover insights and develop solutions that help hundreds of millions of consumers achieve greater financial freedom.

Qualifications:
  • 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.
  • 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:
  • Experience in fraud detection, security, risk, or abuse prevention.
  • Experience with large-scale training, graph systems, and sequential modeling.

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. 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!

Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

About Plaid

Plaid is a financial services company based in New York City. The company builds a technology platform, which enables applications to connect with users' bank accounts. Plaid focuses on enabling consumers and businesses to interact with their bank accounts, check balances, and make payments through financial technology applications. The company was founded in 2013 by Zach Perret and William Hockey. In January 2020, Visa announced that it would acquire Plaid for $5.3 billion. The acquisition was completed in January 2021.
Learn more about Plaid
Size
600 employees
Industry
Founded
2011

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