Senior AI Engineer, Big Data & AI Solutions
About The Position
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. The Senior AI Engineer works at the intersection of big data engineering and AI/ML, building and supporting the data, features, models, and production processes behind fraud detection. The role focuses on large-scale data engineering and production AI/ML, while also contributing to Generative AI and agentic AI solutions that improve engineering workflows and operational efficiency. The engineer builds and enhances Spark/PySpark data and feature pipelines, supports model development and production performance, and strengthens monitoring, observability, and drift detection. The role also applies CI/CD, automated testing, version control, and MLOps practices to improve the reliability and scalability of systems. The position requires professional experience with Apache Spark, Python, CI/CD, and AI-assisted development tools.
Requirements
- 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.
- Professional experience with Apache Spark, Python, and CI/CD, and familiarity with AI-assisted development tools.
Nice To Haves
- 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.
Responsibilities
- 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.
- 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 ongoing optimization and retraining of production models and their supporting pipelines.
- 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, to improve engineering workflows and operational efficiency.
- Abide by Mastercard’s security policies and practices; ensure confidentiality and integrity of accessed information; report suspected security violations or breaches; and complete mandatory security training.
Benefits
- Medical, prescription drug, dental, vision, disability, and 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, prorated based on date of hire.
- 10 annual paid U.S. observed holidays.
- 401(k) with a company match.
- Deferred compensation for eligible roles.
- Fitness reimbursement or on-site fitness facilities.
- Tuition reimbursement eligibility.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
