Machine Learning Engineer - Fraud Data

Overview

Join the Staff Machine Learning Engineer - Fraud Data team  Data team within Plaid’s Fraud organization builds the machine learning systems that power industry‑leading fraud detection products. You will design and build scalable ML infrastructure, lead the evolution of model deployment, monitoring, and observability frameworks, and collaborate closely with ML Infrastructure, Product, and Engineering teams to protect users and customers from fraud.

Remote; open to candidates worldwide.

• Design and build scalable ML infrastructure for Plaid’s fraud detection product.
• Lead the evolution of model deployment, monitoring, and observability frameworks.
• Collaborate with ML Infrastructure, Product, and Engineering teams.
• Mentor engineers and shape the long‑term technical vision and strategy of the Fraud Data team.

• 8+ years total experience, with at least 5 years building and deploying production ML systems.
• Proven experience in machine learning infrastructure/operations.
• Proficiency in Python, PyTorch, Spark, Sage Maker, Airflow, or equivalent technologies.
• Experience in fraud detection, risk modeling, or financial security domains.
• Background in graph machine learning or related techniques (nice to have).

Base salary $192,000 – $400,000 (Zone 1). Compensation varies by location.

Plaid is an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion, sex, sexual orientation, gender identity, age, military or veteran status, disability, or other legally protected characteristics. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process.