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Added 5 mins ago
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The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and…

Mastercard

Senior AI Engineer, Big Data & AI Solutions

O'Fallon, MO, United States

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Job details

Posting language: English

Original job description

Summary

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 Solutions

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 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/PySpark, 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, with 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.

Strong familiarity with AI-assisted development tools such as GitHub Copilot or Claude Code.

-Experience with cloud-based data and AI environments.

Technical Environment

Core / Required

-Apache Spark / PySpark

-Python

-CI/CD

Data & Engineering

-SQL

-Databricks

-Airflow

-Hadoop

-ETL & Data Pipelines

-Feature Engineering

AI/ML & MLOps

-MLOps

-Model Monitoring

-GenAI / LLMs / RAG / Agentic AI

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 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.

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 includ...

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