AI Engineer 2

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

AI Engineer 2

Overview

Mastercard is seeking an AI Engineer II to support the development and deployment of AI solutions that power strategic initiatives within the AI & Data organization. This role provides an opportunity to work on advanced AI technologies, including transformer-based and generative AI models, while contributing to the delivery of scalable, production-ready solutions.

Working closely with Senior, Lead, and Principal AI Engineers, you will help develop, evaluate, and operationalize AI capabilities that address real business challenges. This is a hands-on engineering role focused on building technical expertise, delivering high-quality solutions, and growing into greater levels of ownership and technical leadership.

Role

In this role, you will contribute to the development, testing, and deployment of AI and machine learning solutions across the program.

Key Responsibilities Include

Develop and support AI and machine learning models under the guidance of senior team members

Contribute to the development and evaluation of transformer-based and generative AI solutions, including embeddings, tokenization, fine-tuning, and inference workflows

Build and maintain components of data preparation, feature engineering, and model training pipelines

Assist in creating and managing datasets required for model training, validation, and evaluation

Support the implementation and optimization of machine learning workflows and model-serving solutions

Help integrate AI models into applications, APIs, and production environments

Support model testing, validation, monitoring, and performance analysis to ensure quality and reliability

Apply established software engineering and MLOps best practices, including version control, testing, documentation, and deployment automation

Collaborate with AI engineers, data engineers, software engineers, and product teams to implement AI solutions

Troubleshoot issues related to model performance, data quality, and system functionality

Participate in code reviews, technical discussions, and knowledge-sharing activities

Stay current with emerging AI technologies, frameworks, and engineering best practices

All About You

2–5 years of experience in AI engineering, machine learning engineering, data science, software engineering, or a related technical field

Strong programming skills in Python

Experience using AI/ML frameworks such as PyTorch, TensorFlow, or similar technologies

Foundational understanding of machine learning, deep learning, and AI engineering concepts

Familiarity with transformer architectures, large language models, tokenization techniques, embeddings, and generative AI technologies

Experience working with data processing, feature engineering, and model training workflows

Familiarity with model evaluation techniques and performance measurement

Exposure to cloud-based development environments such as AWS, Azure, or GCP

Understanding of software engineering fundamentals, including testing, version control, CI/CD principles, and code quality practices

Familiarity with APIs and integrating machine learning models into applications is a plus

Knowledge of data structures, algorithms, and scalable computing concepts

Strong analytical and problem-solving skills

Effective communication and collaboration skills, with the ability to work in a cross-functional team environment

Demonstrated ability to learn new technologies quickly and adapt to evolving technical requirements

Bachelor's degree or equivalent practical experience in Computer Science, Engineering, Data Science, Mathematics, or a related field

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.