Responsibilities
● Design and build effective, user-friendly infrastructure, tooling, and
automation to accelerate Machine Learning
● Collaborate with teams to drive the ML technical roadmap
● Collaborate with Machine Learning Engineers and Product Managers to
develop tools to support experimentation, training and production
operations
● Build and maintain data pipelines using tools like Hadoop, Python,
Airflow, and Kafka
● Offer support and troubleshooting assistance for the ML pipeline, while
continuously improving stability along the way
● Build and maintain systems employing an Infrastructure-as-Code
approach
● Own the AWS stack which comprises all ML resources
● Establish standards and practices around MLOps, including
governance, compliance, and data security
● Collaborate on managing ML infrastructure costs