Senior Machine Learning Engineer - Infra/Ops - Fraud

Plaid•New York, NY

2d•$228,960 - $315,360

About The Position

The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions.

Requirements

6+ years of relevant experience, with a strong focus on building, deploying, and scaling production machine learning systems.
Strong experience with ML infrastructure and operations, including production deployment, monitoring, and reliability.
Proven ability to independently own and deliver complex, end-to-end machine learning engineering projects.
Proficiency with Python and experience with ML and data technologies such as PyTorch, Spark, SageMaker, and Airflow.

Nice To Haves

Experience in fraud or risk domains.
Experience in Graph machine learning.

Responsibilities

Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment.
Solve complex technical challenges at the intersection of machine learning, data infrastructure, and production reliability.
Develop foundational ML capabilities that leverage Plaid’s extensive financial network data to detect and prevent fraud.
Collaborate closely with engineers, data scientists, and cross-functional partners across Plaid to deliver high-impact solutions.