Senior ML Engineer - Scalable ML Infra & Production

Plaid; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity compensation

Comprehensive benefits

Job summary

Plaid is seeking a Senior Machine Learning Engineer to own high-performance feature computation and online inference pipelines for production ML systems in fraud detection. You will build observability, monitoring, and debugging capabilities while partnering with ML Infrastructure, Data Science, and Product teams.

You will help scale ML capabilities using Plaid's vast financial network data, ensure reliability, and collaborate across engineers and data scientists to deliver high-impact ML

Qualifications

• 6+ years of experience building, deploying, and scaling production ML systems.
• Experience with ML infrastructure, deployment, monitoring, and reliability.
• Proven ability to independently own end-to-end ML projects.
• Proficiency with Python and ML/data technologies such as PyTorch, Spark, SageMaker, and Airflow.

Responsibilities

• Build and scale machine learning systems powering a fraud detection product at Plaid.
• Address complex challenges at the intersection of ML, data infra and production reliability.
• Develop ML capabilities leveraging Plaid's financial network data to detect fraud.
• Collaborate with engineers, data scientists, and cross-functional partners to deliver high-impact solutions.

Skills

Python

PyTorch

Spark

SageMaker

Airflow

ML infrastructure

Production ML

Tools

PyTorch

Spark

SageMaker

Airflow

Job description

Plaid is seeking a Senior Machine Learning Engineer to own high-performance feature computation and online inference pipelines for production ML systems in fraud detection. You will build observability, monitoring, and debugging capabilities while partnering with ML Infrastructure, Data Science, and Product teams.

You will help scale ML capabilities using Plaid's vast financial network data, ensure reliability, and collaborate across engineers and data scientists to deliver high-impact ML