Lead MLOps Engineer

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Lead MLOps Engineer

The Security Solutions Data Science team is responsible for creating Artificial Intelligence (AI) and Machine Learning (ML) models backing its flagship product. The models generated are production ready and created to back specific products in Mastercard’s authentication and authorization networks. The Data Science team is also responsible for developing automated processes for creating models covering all modeling steps, from data extraction up to delivery. In addition, the processes must be designed to scale, to be repeatable, resilient, and industrialized.

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.

You will be joining a team of Data Scientists and engineers working on innovative AI and ML fraud detection. Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech and payments processing. We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge AI model evaluation and reporting processes.

As a Lead MLOps Engineer, you will:
• Oversee the administration of Databricks clusters and workspaces.
• Bring MLOps expertise to the table, namely within the scope of, but not limited to:
o Model monitoring
o Feature catalog
o Experiment Tracking
o CI/CD pipelines to gatekeep model lifecycle from development to production
• Own and maintain MLOps solutions either by leveraging open-sourced solutions or with a 3rd party vendor
• Build and maintain various executive dashboards that reflect metrics, model build, deploy, and run phases
• Be a technical lead to a team of MLOps engineers

All About You:
• Bachelor's degree in computer science, software engineering, or a similar field. 
• Strong experience with Databricks and ability to architect scalable DE pipelines. Strong experience with Spark
• Experience in cloud technologies and operations
• Experience supporting API’s and Cloud technologies
• Experience with MLOps solutions like MLFlow, Comet, WandB, or other similar frameworks
• Experience with performing data analysis, data observability, data ingestion and data integration. 
• Solid DevOps, SRE, or general systems engineering experience. 
• Hands-on experience in industry standard CI/CD tools like Git/BitBucket, Jenkins, Maven, Artifactory, and Chef. 
• Experience architecting and implementing data governance processes and tooling (such as data catalogs, lineage tools, role-based access control, PII handling) 
• Strong coding ability in Python or other languages like Java, and C++, plus a solid grasp of SQL fundamentals 
Systematic problem-solving approach, coupled with strong communication skills and a sense of ownership and drive.
Nice to have:
• SQL tuning experience. 
• Strong automation experience
• Strong Data Observability experience. 
• Operations experience in supporting highly scalable systems. 
• Self-Motivating and creatively solves software problems and effectively keep the lights on for modeling systems.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.