Senior ML Platform Engineer

Senior ML Platform Engineer

Our Mission

• Build and evolve internal data and machine learning platforms used across IDV Data Science.


• Develop distributed data processing solutions, reusable tooling, and platform capabilities for internal machine learning workflows at scale.


• Improve reliability, performance, automation, and maintainability across the engineering systems and tools we build.


• Collaborate with Data Scientists and engineers to bring machine learning solutions into production.


• Contribute to technical design, architecture, and engineering best practices.


• Mentor teammates and help raise the engineering bar across the organization.

• Strong software engineering background with professional experience in JVM languages; Scala experience is preferred, but strong Java or Kotlin experience is also welcome where paired with a willingness to learn.


• Solid Python development experience.


• Deep understanding of distributed data processing systems, preferably Apache Spark.


• Experience designing and operating large-scale data pipelines, platforms, or machine learning systems.


• Knowledge of MLOps, Data Engineering, and data warehousing concepts.


• Strong problem-solving skills, a pragmatic engineering mindset, and natural curiosity for learning new technologies and approaches.


• Excellent communication and collaboration skills.

• Experience with, or interest in, functional programming in a strongly typed setting.


• Databricks experience.


• AWS or other cloud platform experience.


• Experience with modern AI-assisted development tools such as GitHub Copilot, Claude, or similar.

• Work on large-scale systems that help customers combat fraud and build trust in digital commerce.


• Influence the architecture and direction of internal machine learning platforms and tools used by Data Science teams.


• Collaborate with experienced Data Scientists, Engineers, and Architects.


• Tackle challenging problems involving distributed systems, data, and machine learning at scale.


• Be part of a team that values technical excellence, ownership, curiosity, learning, and continuous improvement.

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.