MLOps Engineering Manager

Mastercard - O'Fallon, MO

Full-time - Mid Level

O'Fallon, MO

Credit Intermediation and Related Activities

About the position

The MLOps Engineering Manager at Mastercard will lead the AI Fraud Solutions team in developing and maintaining machine learning operations that protect the payments ecosystem against fraud. This role focuses on building monitoring pipelines, ensuring model performance, and facilitating the deployment of scalable tools for machine learning training and inference. The position is pivotal in transitioning Mastercard into an AI-driven organization, requiring expertise in data pipelines and collaboration with cross-functional teams.

Responsibilities

• Designing the monitoring strategy for offline AI models deployed in production to ensure system observability and swift issue response.
• Supporting model refreshes to ensure correct deployment in production.
• Creating deployment reports for key stakeholders and customers.
• Assisting in the deployment of scalable tools and services for machine learning training and inference in production.
• Evaluating new technologies to enhance performance, maintainability, and reliability of machine learning systems, including facilitating proof-of-concepts.
• Communicating with stakeholders to build requirements and track progress against issues that may arise.
• Developing systems for data versioning, model management, and deployment strategies to ensure models are manageable, debuggable, and deployable.

Requirements

• Experience building data pipelines as a ML DevOps Engineer or Data Engineer (or equivalent).
• Strong proficiency with open-source tools, containerization, orchestration tools, and experience with data versioning and model management tools.
• Experience working with various database systems.
• Ability to translate business needs to technical requirements.
• Exposure to machine learning methodology, best practices, modeling approaches, and frameworks.
• Experience working with cross-functional teams in executing projects.
• Strong organizational skills with the ability to learn quickly and multi-task across multiple projects in a fast-paced environment.
• Experience in a similar role or as a data scientist.
• Bachelor's or master's degree in engineering and/or equivalent professional experience.

Benefits

• Insurance (including medical, prescription drug, dental, vision, disability, life insurance)
• Flexible spending account and health savings account
• Paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave)
• 10 annual paid sick days
• 10 or more annual paid vacation days based on level
• 5 personal days
• 10 annual paid U.S. observed holidays
• 401k with a best-in-class company match
• Deferred compensation for eligible roles
• Fitness reimbursement or on-site fitness facilities
• Eligibility for tuition reimbursement
• Gender-inclusive benefits
• And many more.