Machine Learning Engineer - Fraud Data

Position: Staff Machine Learning Engineer - Fraud Data
Join to apply for the Staff Machine Learning Engineer - Fraud Data role at Plaid

We believe that the way people interact with their finances will drastically improve in the next few years. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, and many of the Fortune 500 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.

Responsibilities

• Design and build scalable ML infrastructure for Plaid’s fraud detection product

• Lead the evolution of model deployment, monitoring, and observability frameworks to ensure high reliability and performance at scale

• Collaborate closely with teams across ML Infrastructure, Product, and Engineering to deliver robust systems that protect users and customers from fraud

• Mentor other engineers and help shape the long‑term technical vision and strategy of the Fraud Data team

Qualifications

• 8+ years total experience, with at least 5 years building and deploying production ML systems

• Proven experience in machine learning infrastructure/operations

• Demonstrated technical leadership and architectural vision, driving systems from concept to production

• Proficiency in Python, PyTorch, Spark, Sage Maker, and Airflow, or equivalent technologies

• Nice to have - experience working in fraud detection, risk modeling, or financial security domains

• Nice to have - background in graph machine learning or related techniques

Compensation

The target base salary for this position ranges from $253,200 to $400,000 per year in Zone 1. The target base salary will vary based on the job’s location. Zone 1 includes New York City and San Francisco Bay Area. Zone 2 includes Los Angeles, Seattle, Washington D.C. Zone 3 includes Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego. Zone 4 includes Raleigh‑Durham and all other U.S. cities.

Remote candidates are welcome for this role.

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 .

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