Senior Machine Learning Engineer

Responsibilities

• Build and scale machine learning systems supporting a growing fraud detection product.
• Develop high-performance feature computation and online inference pipelines for production ML systems.
• Build observability, monitoring, reliability, and automated debugging capabilities.
• Develop foundational ML capabilities using Plaid’s financial network data to detect and prevent fraud.
• Solve technical challenges spanning machine learning, data infrastructure, and production reliability.
• Own and deliver complex end-to-end machine learning engineering projects.
• Collaborate with engineers, data scientists, ML Infrastructure, Product, and other cross-functional partners.

Requirements

• 6+ years of relevant experience focused 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 PyTorch, Spark, SageMaker, and Airflow.
• Experience in fraud or risk domains is preferred.
• Experience in graph machine learning is preferred.

Benefits

• Comprehensive medical, dental, vision, and 401(k) benefit plan.
• Equity and/or commission may be provided as additional compensation depending on the position.
• Pay and benefits are subject to change according to applicable compensation or benefit plans.