Senior ML Platform Engineer
Salary not listed • Budapest, Hungary • Full-time
Posted 1mo ago
About the job
Mastercard Identity Verification is seeking a Senior ML Platform Engineer to join their Budapest team. This role focuses on building, developing, and maintaining internal platforms, tools, and distributed data processing capabilities to support reliable, production-grade machine learning workflows. The position is a blend of software, data, and ML engineering, aimed at creating internal capabilities that empower Data Scientists and Engineers to build, run, and enhance machine learning systems at scale. The ideal candidate is a skilled software engineer adept at solving complex data and ML engineering challenges, writing high-quality code, and constructing robust, scalable systems.
Responsibilities
- Build and evolve internal data and machine learning platforms for IDV Data Science.
- Develop distributed data processing solutions, reusable tooling, and platform capabilities for large-scale internal ML workflows.
- Enhance the reliability, performance, automation, and maintainability of engineering systems and tools.
- Collaborate with Data Scientists and engineers to deploy machine learning solutions into production.
- Contribute to technical design, architecture, and engineering best practices.
- Mentor teammates and elevate engineering standards across the organization.
Requirements
- Strong software engineering background with professional experience in JVM languages (Scala preferred, or Java/Kotlin with 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 curiosity for new technologies.
- Excellent communication and collaboration skills.
Benefits
- Work on large-scale systems to combat fraud and build trust in digital commerce.
- Influence the architecture and direction of internal ML platforms and tools.
- Collaborate with experienced Data Scientists, Engineers, and Architects.
- Tackle challenging problems involving distributed systems, data, and ML at scale.
- Be part of a team valuing technical excellence, ownership, curiosity, learning, and continuous improvement.