Machine Learning Engineer

The Services global product team is seeking a Machine Learning Engineer to accelerate the development of Payments AI solutions within the Data, Analytics, and AI product suite. The goal of the Payments AI Solutions team is to build AI products that drive Smarter Decisions and Better Outcomes for customers, applying AI responsibly, and leveraging in-house and 3rd party assets and capabilities effectively to maximize ROI for the program.

Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features. The range of work you will encounter varies from building intuitive, responsive UIs to designing backend data models, architecting data flows, and beyond. There are no rigid organizational structures, and each team uses processes that work best for its members and projects.

Position Responsibilities:

As a Machine Learning Engineer, you will:
• Build and deploy AI solutions that should work at scale.
• Build appropriate data pipelines to support model deployments.
• Optimize large models for efficiency and scalability.
• Monitor the AI models and applications that are deployed.
• Lead and own everything around Machine Learning Operations.
• Prepare appropriate documentation of the model deployment and processes.
• Conduct root cause analysis of data, pipeline and other processes.
• Conduct data analysis for different use-cases.
• Conduct data extraction, data analysis, data cleaning, preparation, modeling, and evaluation.
• Work as a member of an agile team to design, build, test, and deploy new products and features.
• Participate in code reviews, model review, testing and debugging for high quality product.
• Support building prototypes, and proof-of-concepts.
• Push for better Development Practices, better Code, better Solutions.
• Collaborate with internal teams and other teams across the company.
• Proactively understand stakeholder needs, goals, expectations and viewpoints to deliver results.

All about you:
• Proven experience in developing and deploying Machine learning and Deep learning solutions.
• Deep understanding of different Machine learning, Deep learning, and AI algorithms.
• High proficiency in using Python and R.
• Hands on experience on ML Frameworks (Scikit learn) and Deep Learning Framework (TensorFlow, PyTorch).
• Solid experience with SQL, Hadoop/ Snowflake/ Databricks databases
• Good understanding of Cloud technology.
• Building and maintaining ML production pipelines.
• Curious, Critical thinker, good hacking skills and scientific reasoning.
• Strong familiarity with Software engineering practices.
• Not afraid to ask questions and propose new ideas
• Strong technologist eager to learn new technologies and frameworks.

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.