Description
Mastercard's Security Solutions Data Science team develops AI and machine learning capabilities to protect the global payments ecosystem from fraud and cyber threats. 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.
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
- 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.
- Hands-on professional experience with Apache Spark/PySpark, Python, CI/CD, and familiarity with AI-assisted development tools.
- 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.
Benefits
- 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
- 401k with a best-in-class company match
- Deferred compensation for eligible roles
- Fitness reimbursement or on-site fitness facilities
- Eligibility for tuition reimbursement