Senior AI Engineer

MasterCard; O’Fallon (MO); On-site; USD 115,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401k with company match

Paid time off

Job summary

Mastercard’s Security Solutions Data Science team builds AI and ML capabilities to safeguard the global payments ecosystem from fraud and cyber threats. The Senior AI Engineer works at the intersection of AI and big data engineering to enhance models, data assets, and operations powering fraud detection.

You will collaborate with Data Scientists and Engineers to strengthen feature engineering, monitor models, and deliver AI-driven solutions that improve performance and efficiency.

Qualifications

• Master’s degree or Bachelor’s with relevant experience in AI/DS/engineering.
• Proficiency in Python, PySpark, SQL and distributed data processing.
• Hands-on experience with feature engineering and large-scale data processing.
• Experience with Databricks, Airflow, Hadoop, Linux/Unix and cloud-native tech.
• Understanding of ML/DL techniques and model deployment, monitoring, and optimization.
• Knowledge of MLOps concepts including CI/CD and version control.
• Ability to communicate technical concepts and collaborate across teams.

Responsibilities

• Support machine learning models for cyber-attacks, fraud and decision intelligence.
• Create data pipelines and feature engineering workflows for model development.
• Process and analyze large-scale datasets to improve model inputs.
• Strengthen monitoring, observability, and drift detection in production.
• Apply automation and MLOps to improve reliability and scalability.
• Develop AI-powered solutions addressing engineering challenges and operations.
• Collaborate with Data Scientists, Engineers and Product teams to productionize capabilities.
• Contribute ideas to improve model performance and team productivity.

Skills

Python

PySpark

SQL

Data processing

Feature engineering

Model deployment

MLOps

Cloud technologies

Education

Master’s degree in CS/AI/DS

Bachelor’s degree in CS/AI/DS

Tools

Databricks

Airflow

Hadoop

Linux/Unix

Cloud-native technologies

Job description

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 Senior AI Engineer Overview The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard's Safety Net product, the team creates and enhances models that analyze billions of transactions and identify suspicious activity in real time. As a Senior AI Engineer, you will work at the intersection of AI engineering and big data engineering, helping improve the models, data assets, and operational processes that power fraud detection. You will collaborate closely with Data Scientists and Engineers to strengthen feature engineering, advance model monitoring capabilities, and deliver AI-driven solutions that improve performance and efficiency.

Role

• Support machine learning models that help detect cyber-attacks, fraud and improve decision intelligence.
• Create data pipelines and feature engineering workflows that enable model development and evaluation.
• Process and analyze large-scale datasets to uncover insights and improve model inputs.
• Strengthen monitoring, observability, and drift detection capabilities across production environments.
• Apply automation and MLOps practices to improve reliability, efficiency, and scalability.
• Develop AI-powered solutions that address engineering challenges and streamline operational processes.
• Partner with Data Scientists, Engineers, and Product teams to bring new capabilities into production.
• Contribute ideas that improve model performance, operational visibility, and team productivity.

Required Qualifications

• Master’s degree with 2+ years of relevant experience, or Bachelor’s degree with 5+ years of relevant experience, in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience will also be considered.
• Proficiency in Python, PySpark, SQL, and distributed data processing.
• Hands-on experience with feature engineering, large-scale data processing, and analytics.
• Hands-on experience with Databricks, Airflow, Hadoop, Linux/Unix, cloud-native technologies
• Understanding of machine learning and deep learning techniques.
• Understanding of model deployment, evaluation, monitoring, and optimization.
• Knowledge of MLOps concepts including testing, automation, CI/CD, and version control.
• Ability to communicate technical concepts and collaborate across teams.

Preferred Qualifications

• Fraud, cybersecurity, payments, or risk management domains.
• Experience with Generative AI, LLMs, RAG, or agentic AI applications.
• Familiar with AI-assisted development tools such as GitHub Copilot, or Claude Code.
• Experience working with cloud-based data and AI environments.

Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role.

In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [e-mail] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

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.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience.

Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more.

Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.

Pay Ranges O'Fallon, Missouri: $115,000 - $184,000 USD

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.