Lead AI 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 AI 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.

Overview

Mastercard's Security Solutions organization develops and delivers industry-leading identity, fraud prevention, and cybersecurity solutions to customers around the world.

Within the Identity Verification (IDV) Data Science organization, the Machine Learning Platform (MLP) team builds and operates the platforms, tooling, and infrastructure that enable Data Scientists and AI Engineers to develop, deploy, and scale machine learning solutions.

We are looking for a Lead AI Engineer to join our Budapest office. This position is highly technical in nature, where you will design, develop, and scale the platforms, data pipelines, and machine learning infrastructure that power AI and machine learning solutions across Identity Verification products.

Our ideal candidate combines strong software and data engineering fundamentals with hands-on experience building large-scale machine learning systems. You should be passionate about designing scalable platforms, automating complex workflows, and enabling Data Science teams to deliver reliable, production-ready AI solutions.

Your ideal job should be one where you work in a small team and are empowered to make yourself and your team more productive on a daily basis. You should want to be part of a team where your desire to grow and learn is valued and aptly rewarded; where using and contributing to open source are looked upon as an asset; where innovating and executing are core to your team's beliefs.

In this role, You will:

- Be part of a Machine Learning Platform engineering team.
- Work with cutting-edge AI, machine learning, and big data platforms and technologies.
- Design complex, scalable, maintainable, and efficient systems.
- Build and maintain data pipelines, machine learning infrastructure, and platform capabilities that support Data Science solutions.
- Automate and optimize Data Science tasks, machine learning workflows, and engineering processes.
- Drive improvements in platform reliability, scalability, performance, observability, and operational excellence.
- Be responsible for the performance and automated testing of your code.
- Provide technical leadership for development tasks and projects.
- Build cross-team collaboration and architecture ownership of the products and platforms supported by the team.
- Independently analyze, propose, and develop solutions for complex technical challenges and issues.
- Participate in technical design reviews, architecture discussions, and technology strategy.
- Communicate closely and effectively with engineering management, Data Scientists, architects, and peers to gather and understand requirements, share project status, and resolve unexpected issues.
- Ensure and enforce adherence to standards and procedures that result in an environment compliant with information security policies.
- Mentor junior and senior colleagues and contribute to engineering excellence across the organization.

All About You

- Relevant senior or lead-level experience in software, data, or AI engineering.
- Strong programming skills in Python and experience with Java, Scala, or similar languages.
- Experience working with large-scale distributed data processing platforms or big data query engines, preferably Apache Spark.
- Experience with Databricks is a plus.
- Experience designing, building, and operating large-scale data platforms and processing systems.
- Experience building and supporting machine learning systems in production environments.
- Strong understanding of machine learning concepts, including feature engineering, model training, deployment, and monitoring.
- Experience with cloud platforms and cloud-native architectures (AWS preferred).
- Experience designing complex systems, architectures, and data flows.
- Strong understanding of distributed systems, scalability, reliability, and performance optimisation.
- Experience with CI/CD practices, infrastructure automation, testing, and platform operations.
- Strong understanding of software development lifecycle processes and tools, including Jira and Confluence.
- Proven ability to write clean, maintainable, and well-tested code that follows engineering best practices and coding standards.
- Experience using modern software engineering practices and AI-assisted development tools to improve engineering productivity.
- Mature understanding and technical leadership of object-oriented design, distributed systems, data structures, networking, database design, and software architecture.
- Strong communication skills and the ability to collaborate effectively with engineers, Data Scientists, product teams, and business stakeholders.
- Proven ability to provide technical leadership and mentor other engineers.
- A philosophy of iteration and continuous improvement (Agile, Scrum).

It also helps if you are:

- Collaborative. We do our best work as a team and value openness, support, and constructive feedback.
- Curious. You enjoy learning new technologies and continuously expanding your expertise in AI, machine learning, and platform engineering.
- Innovative. You challenge assumptions and explore new approaches to solving difficult problems.
- Responsible. You care about building secure, reliable, and maintainable systems that operate at scale.
- Hands-on. You enjoy solving technical challenges and leading by example through your own engineering contributions.
- Impact-focused. You care about enabling Data Scientists and engineers to deliver better outcomes for customers.

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.