Senior AI Engineer
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 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.
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.
- 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.
Nice To Haves
- 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.
Responsibilities
- 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.
Benefits
- insurance (including medical, prescription drug, dental, vision, disability, life insurance)
- flexible spending account and health savings account
- 16 weeks of new parent leave
- up to 20 days of bereavement leave
- 80 hours of Paid Sick and Safe Time
- 25 days of vacation time
- 5 personal days
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
