Senior Machine Learning Engineer (Infrastructure/Operations - Fraud)

Plaid; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Office locations SF

Office locations NYC

Office locations Raleigh-Durham

Health benefits

Fertility support

Mental health support

Parental leave

Home office stipend

Daycare support

Commuting benefits

Job summary

Plaid is seeking a Senior Machine Learning Engineer to own the development of high-performance feature computation and online inference pipelines powering production ML systems at scale. You will build observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability.

You will partner with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver

Qualifications

• 6+ years of relevant experience in ML systems.
• Proficiency with Python and ML tech such as PyTorch, Spark, SageMaker, Airflow.
• Ability to independently own end-to-end ML engineering projects in production.
• Strong experience with ML infrastructure, production deployment, monitoring, and reliability.
• Experience in Graph machine learning and fraud/risk domains.

Responsibilities

• Own development of feature computation and online inference pipelines for production ML systems.
• Build observability, monitoring, and automated debugging capabilities.
• Collaborate with ML Infrastructure, Data Science, and Product teams on critical initiatives.
• Scale ML systems for a growing fraud detection product in a fast-paced environment.
• Solve complex challenges at the intersection of ML, data infra, and production reliability.
• Develop foundational ML capabilities leveraging Plaid’s data to detect and prevent fraud.

Skills

Python

PyTorch

Spark

SageMaker

Airflow

Graph ML

Fraud/Risk

Production Deployment

Monitoring

End-to-End ML Projects

Job description

• 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
• 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

Benefits

• Vibrant offices in SF, NYC, and Raleigh-Durham—with catered meals, happy hours, and clubs to keep you connected
• Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
• Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft

6+ years of relevant experience, with a strong focus on building, deploying, and scaling production machine learning systemsProficiency with Python and experience with ML and data technologies such as PyTorch, Spark, SageMaker, and AirflowProven ability to independently own and deliver complex, end-to-end machine learning engineering projectsStrong experience with ML infrastructure and operations, including production deployment, monitoring, and reliabilityExperience in Graph machine learningExperience in fraud or risk domains