Senior AI Engineer

Mastercard; Dublin; On-site; EUR 120,000 - 170,000; Full time

Job summary

Mastercard is seeking a Senior AI Engineer to design, build, and deploy production-grade AI solutions. You will work on transformer-based models and integrate them into APIs and downstream systems.

You will collaborate with product, data, and engineering teams, applying MLOps and software engineering best practices for scalable, reliable AI platforms. The role offers opportunities for technical leadership as the system evolves.

Qualifications

• Proven experience in developing production AI solutions.
• Strong proficiency in Python and ML frameworks (PyTorch/TensorFlow).
• Hands-on with transformer-based models and modern ML pipelines.
• Experience building data pipelines, feature engineering, and data management.
• Familiarity with cloud platforms (AWS/Azure/GCP) and ML tooling.
• Knowledge of MLOps: deployment, monitoring, and lifecycle management.
• Solid software engineering fundamentals: version control, testing, and code quality.

Responsibilities

• Design, build, and deploy AI/ML models to address business problems.
• Advance transformer-based and generative AI models including fine-tuning and evaluation.
• Develop data pipelines, feature engineering, and training workflows with data teams.
• Implement model serving and integrate models with APIs and downstream apps.
• Apply MLOps practices: experiment tracking, testing, monitoring, and performance eval.
• Collaborate with product and engineering on requirements and architecture.
• Troubleshoot and optimize AI systems in production; stay current with AI advances.

Skills

Python

PyTorch

TensorFlow

Machine Learning

Transformer models

MLOps

Cross-functional collaboration

Code quality

Education

Bachelor's degree or equivalent in CS/Engineering/Data Science

Tools

AWS

Azure

GCP

Git

Job description

Title And Summary

Senior AI Engineer

Overview

Mastercard is seeking a Senior AI Engineer to design, build, and deploy high‑quality AI solutions that support key business and product initiatives. This role is hands‑on and delivery‑focused, contributing directly to the development of production AI systems while collaborating closely with product, data, and engineering partners. As a Senior AI Engineer, you will work on well‑scoped AI initiatives, applying advanced machine learning and software engineering practices to move models from experimentation into reliable, performant production systems. This role represents a critical technical contributor level, with opportunities to grow toward technical leadership and broader system ownership.

Key Responsibilities

• Design, develop, and deploy AI and machine learning models to solve defined business and product problems.
• Contribute to the development and optimization of transformer‑based and generative AI models, including fine‑tuning, evaluation, and inference workflows.
• Build and maintain data pipelines, feature engineering logic, and training workflows in collaboration with data engineering teams.
• Implement model serving and inference solutions, integrating models into downstream applications and APIs.
• Apply MLOps best practices, including experiment tracking, versioning, automated testing, monitoring, and model performance evaluation.
• Participate in code reviews, design discussions, and technical planning to ensure high‑quality, maintainable solutions.
• Collaborate with product managers and stakeholders to translate requirements into technical implementations.
• Support troubleshooting and performance tuning of models and AI systems in production environments.
• Continuously improve technical skills and stay current with advances in AI, ML frameworks, and engineering practices.

All About You

• Solid experience developing machine learning or AI solutions and deploying them into production environments.
• Strong proficiency in Python and experience with ML frameworks such as PyTorch and/or TensorFlow.
• Hands‑on experience with transformer‑based models (e.g., BERT‑style encoders, generative models, embeddings, or similar architectures).
• Experience working with data pipelines and datasets, including data preparation, feature engineering, and training data management.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and cloud‑based ML tooling.
• Working knowledge of MLOps practices, including model deployment, monitoring, and lifecycle management.
• Strong software engineering fundamentals, including version control, testing, and code quality practices.
• Ability to collaborate effectively within cross‑functional teams and follow established architectural and engineering standards.
• Clear communicator with a growth mindset and interest in progressing toward broader technical ownership.
• Bachelor’s degree or equivalent practical experience in computer science, engineering, data science, or a related field.

Corporate Security Responsibility

• 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.
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.