Senior AI Engineer

Who you are

• 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

What the job involves

• 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
• In this role, you will be responsible for building and operationalizing AI solutions under the guidance of Lead and Principal engineers
• 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
• 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

The application process

• End Date: July 28, 2026