Machine Learning Engineer - Fraud Data

Job Description

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.

We’re the Data team within Plaid’s Fraud organization, and we’re on a mission to stop fraud before it happens. Our team builds the machine learning systems that power Plaid’s most advanced fraud detection products, harnessing the scale and richness of Plaid’s network data to protect consumers and businesses alike. We own the full ML lifecycle — from feature pipelines and model training to deployment and monitoring — ensuring our systems are reliable, scalable, and ready to support hundreds of customers as Plaid continues to grow.

As a Machine Learning Engineer on Plaid’s Fraud Data team, you’ll play a key role in shaping the future of fraud prevention. You’ll develop new features and machine learning models that enhance the accuracy and effectiveness of our fraud detection systems, while building reliable data and model pipelines to power both experimentation and production workflows. Working closely with data science, infrastructure, and product teams, you’ll help design and deliver scalable, high-quality ML systems that protect Plaid’s customers at scale. You’ll also have the opportunity to explore and prototype GenAI-driven capabilities that push the boundaries of our fraud modeling and investigation tools.

The target base salary for this position ranges from $202,800/year to $279,600/year in Zone 1. The target base salary will vary based on the job's location.

Our geographic zones are as follows:

Zone 1 - New York City and San Francisco Bay Area

Zone 2 - Los Angeles, Seattle, Washington D.C.

Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego

Zone 4 - Raleigh-Durham and all other US cities

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.

Responsibilities

Build and deploy end-to-end ML solutions — from feature engineering to production deployment

Scale and optimize machine learning systems in a real-world, high-traffic environment

Explore and apply cutting-edge LLMs and generative AI to strengthen fraud prevention and investigation

Grow your career in a fast-paced, collaborative environment

Qualifications

3-5 years total experience, with at least 2 years of hands-on work in ML systems, modeling, or data engineering

Proven experience building and deploying end-to-end machine learning system

Strong foundation in Python and core ML principles

Demonstrated curiosity and adaptability — comfortable working across both modeling and infrastructure

Nice to have - experience in fraud detection, risk modeling, or related domains

Nice to have - familiarity with large language models (LLMs) or generative AI frameworks

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!

Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.

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