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, Big Data & AI SolutionsOverviewThe 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 develops and enhances models that analyze billions of transactions and identify suspicious activity.
As a Senior AI Engineer, you will work at the intersection of big data engineering and AI/ML, helping build and support the data, features, models, and production processes behind fraud detection.
Ideal Candidate Profile
You are a big data and AI/ML engineer who has used Apache Spark in a professional environment and has hands-on experience working within CI/CD-driven engineering environments.
You understand how large-scale data moves from raw inputs through data and feature pipelines into machine learning models, and how those models are deployed, monitored, and improved in production.
Large-scale data → Spark/PySpark → Data & Feature Pipelines → ML models
→ Production Deployment→ CI/CD→Monitoring & Drift Detection → Optimization
& Retraining
Experience with Generative AI, RAG, LLMs, or agentic AI is valuable, but the foundation for this role is large-scale data engineering and production AI/ML.
What You’ll Do
Big Data & Feature Engineering
- Build and enhance large-scale data and feature pipelines using Apache
Spark/PySpark, Python, and SQL.
- Transform high-volume data into reliable features and inputs that support
machine learning models.
Production AI/ML
- Partner with Data Scientists and Engineers to support model development,
evaluation, deployment, and production performance.
- Strengthen model monitoring, observability, and drift detection to identify
changes in model or data performance.
- Support the ongoing optimization and retraining of production models and
their supporting pipelines.
MLOps & AI Engineering
- Apply CI/CD, automated testing, version control, and MLOps practices to
improve reliability and scalability.
- Develop AI-powered solutions, including Generative AI and agentic
approaches, that improve engineering workflows and operational efficiency.
Required Qualifications
This role requires hands-on professional experience with Apache Spark, Python, CI/CD, and familiarity with AI-assisted development tools.
- 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.
- Hands-on professional experience with Apache Spark/PySpark in large-scale
or distributed data-processing environments.
- Hands-on experience with CI/CD practices, including automated integration,
testing, or deployment workflows.
- Proficiency with Python and SQL and experience building ETL, data, or feature
engineering pipelines.
- Experience working with large-scale data and technologies such as
Databricks, Airflow, Hadoop, Linux/Unix, or comparable data platforms.
- Understanding of the production machine learning lifecycle, including model
development, deployment, monitoring, evaluation, and optimization.
- Strong problem-solving, communication, and cross-functional collaboration
skills.
Preferred Qualifications
- Experience supporting production AI/ML systems, including model
monitoring, observability, or drift detection.
- Experience in fraud, cybersecurity, payments, or risk management.
- Experience with Generative AI, LLMs, RAG, or agentic AI.
- Familiarity with AI-assisted development tools such as GitHub Copilot or
Claude Code.
- Experience with cloud-based data and AI environments.
Technical Environment
- Apache Spark / PySpark (required)
- Python (required)
- CI/CD (required)
- SQL
- Databricks
- Airflow
- Hadoop
- ETL & Data Pipelines
- Feature Engineering
- MLOps
- Model Monitoring
- GenAI / LLMs / RAG / Agentic AIMastercard 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 reasonable_accommodation@mastercard.com 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.
Pay Ranges
O'Fallon, Missouri: $115,000 - $184,000 USDFrom the posting on Mastercard's job site. Read the original before you apply.