Senior ML Platform Engineer

About the role

We are looking for a Senior ML Platform Engineer to join our Budapest team. This hands‑on role focuses on building, developing and maintaining internal platforms, tools and distributed data processing capabilities that enable reliable, production‑grade machine learning workflows.

Key responsibilities

• 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.

Required profile

• Strong software engineering background with professional experience in JVM languages; Scala preferred, Java or Kotlin also acceptable.
• 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, pragmatic engineering mindset, and curiosity for learning new technologies.
• Excellent communication and collaboration skills.

What we offer

• 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.