Lead ML Engineer Job Opportunity at Mastercard

Join Mastercard, a global leader in payments and technology, in our mission to reshape the digital economy in a way that benefits everyone. Our focus is on making transactions safe, simple, smart, and accessible through the use of cutting-edge technologies. By leveraging secure data and networks, partnerships, and passion, we strive to help individuals, financial institutions, governments, and businesses achieve their full potential.

Our Purpose

We are dedicated to connecting and powering an inclusive, digital economy that benefits everyone, everywhere. Our decency quotient (DQ) influences our culture and reflects in everything we do, both internally and externally. We promote a culture of inclusion, fostering respect for individual strengths, views, and experiences. Our diverse team helps us make better decisions, drive innovation, and deliver superior business results.

Job Title: Lead ML Engineer

The Lead ML Engineer will report to the Director of Applied AI and collaborate with the TST Applied AI team. This role is integral to scaling AI impact by transforming prototypes into production-grade AI pipelines, maintaining active models, and contributing to Mastercard's AI platform and engineering best practices.

Key Responsibilities

Transform Prototypes into Production-Grade Models

• Work with data scientists and AI strategists to develop requirements for production models.
• Design and develop robust applications for managing production models.
• Collaborate with data governance and technical teams to ensure compliance with Mastercard AI and engineering standards.

Maintain Models in Production

• Manage the complete CI/CD cycle for live models, including testing and deployment.
• Oversee label feedback and model retraining processes.
• Develop logging, alerting, and remediation strategies for handling model errors.
• Work with data scientists to design and develop drift detection and accuracy measurements for live models.

Contribute to AI Platform and Engineering Practices

• Collaborate with DS and ML engineering leadership to develop coding standards and practices across the applied AI team.
• Research, test, and train the team on leading-edge AI platforms including auto ML libraries, graph databases, and cloud execution frameworks.
• Contribute to the team’s AI infrastructure strategy and management.

Qualifications

• 4+ years of industry experience in engineering, with at least 2 years in data science or ML engineering.
• Strong experience in Python.
• Experience in data product development, analytical models, and model governance.
• Familiarity with AI workflow management tools such as Airflow, Kedro, or Luigi.
• Knowledge in statistical modeling, machine learning algorithms, and predictive analytics.
• Highly structured and organized work planning skills.
• Strong understanding of the AI development lifecycle and Agile practices.
• Proficiency in big data technologies like Hadoop, Spark, or similar frameworks. Experience with graph databases is a plus.
• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud.
• Proven track record of delivering data products in environments with strict adherence to security and model governance standards.
• Bachelor's degree in computer science, analytics, mathematics, statistics, economics, industrial engineering, or physical sciences.

Mastercard is an inclusive Equal Employment Opportunity employer. We consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, or veteran status, or any other characteristic protected by law.

If you require accommodations or assistance to complete the online application process, contact and specify the type of accommodation or assistance you need. Please avoid including any medical or health information in your email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks come with inherent risk to the organization. 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