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AI Engineer II

2 weeks ago

Singapore Mastercard Full time

Job Title:

AI Engineer II

Overview:

Overview
As an AI Engineer on the AI Foundations team, you will build intelligent data products and solutions leveraging vast datasets from retail, restaurants, financial institutions, and other consumer-focused businesses. Your mission will be to develop high-performance AI and data systems that apply cutting-edge machine learning — including deep learning — to unlock insights from big data while upholding the highest standards of data privacy and security.
You will design and implement scalable analytical solutions that process billions of transactions, as well as create intuitive front-end visualizations that help businesses harness the full value of their data.
In this role, you will also have the opportunity to design innovative AI-driven solutions, identify opportunities to meet business and client needs quantitatively, and deliver data-driven recommendations through initiatives such as automated data pipelines, large-scale model deployment, and distributed job execution using modern frameworks like Spark, Hive, and Impala.

Job Description
In this role, you will:

• Build, deploy, and maintain production-grade AI applications and data processing pipelines.

• Apply test-driven development (TDD) principles and leverage testing frameworks to ensure robust, high-quality code.

• Collaborate closely with product managers, data scientists, engineers, and stakeholders to translate business requirements into scalable technical solutions.

• Conduct proofs of concept (POCs) to evaluate and integrate emerging technologies and methodologies.

• Work effectively within a diverse, cross-functional, and geographically distributed project team.

Qualifications

• Bachelor's or Master's degree in Computer Science, Applied Mathematics, Engineering, or a related field.

• 2+ years of hands-on experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or in a related data solutions role.

• Proven experience in deploying machine learning models, APIs, or web applications to production environments.

• Strong proficiency in Python and SQL, with Java experience considered a plus.

• Familiarity with cloud-native big data frameworks such as Hadoop, YARN, Spark, Hive, Impala, NiFi, and Airflow.

• Experience deploying solutions in cloud platforms such as AWS, Cloudera, or Databricks, and integrating data visualization tools like Tableau, Power BI, or Databricks SQL dashboards.

• Working knowledge of software engineering best practices including Git, Jira, and DevOps workflows.

• Experience in microservices architecture, data modeling, data monitoring, dashboarding, and data warehousing concepts.To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.