Mastercard
Overview
Mastercard's AI Center of Excellence (AI COE) is seeking an AI Engineer to lead a team building production grade Agentic AI and traditional AI/ML solutions across the breadth of Mastercard's business. You'll lead the development of prototypes and evolve them into secure, compliant, highly available systems at global scale. This role is ideal for an engineer early in their career who's eager to learn fast, ship meaningful features, and grow under the mentorship of senior engineers in a regulated environment. The Role
As a key contributor to our AI and ML initiatives, you will: Contribute to well-defined prototype efforts and deliver production-ready features with high-quality code, tests, and CI/CD practices. Build core components for Agentic AI systems including RAG, embeddings, vector search, and tool/function calling, with guidance from senior engineers. Enhance model evaluation frameworks (offline/online, golden sets, HIL), monitor key metrics (quality, latency, cost, safety), and drive data-informed improvements. Collaborate on data ingestion, contracts, and catalog usage, ensuring compliance with privacy and access policies. Implement observability tools, guardrails, and cost controls; follow secure coding and Responsible AI practices for safety and auditability. Work cross-functionally with product, design, and platform teams; contribute to agile processes, documentation, and peer reviews. All About You
BS/MS in Computer Science, Data Science, or equivalent practical experience. Proficient in Python, REST, SQL, Git, Docker, and CI/CD workflows. Familiarity with LLMs, prompting, embeddings, RAG, and ML tools like PyTorch/TensorFlow. Exposure to major cloud platforms (Azure, AWS, GCP), data lakes/warehouses, and event-driven systems (e.g., Spark, Kafka). Strong coding practices, iterative development mindset, and clear written/verbal communication. Professional hands-on experience building services, ML features, or GenAI applications. Hands-on with Agentic AI frameworks, prompt management, and evaluation tooling. Understanding of Responsible AI and safety/guardrail systems. Knowledge of Cloudera AI, Databricks, Spark, Delta/Unity Catalog, or similar stacks. Portfolio of open-source contributions, hackathons, or published work. Job Posting Window
Applications for this job posting will be accepted on an ongoing basis.
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Mastercard's AI Center of Excellence (AI COE) is seeking an AI Engineer to lead a team building production grade Agentic AI and traditional AI/ML solutions across the breadth of Mastercard's business. You'll lead the development of prototypes and evolve them into secure, compliant, highly available systems at global scale. This role is ideal for an engineer early in their career who's eager to learn fast, ship meaningful features, and grow under the mentorship of senior engineers in a regulated environment. The Role
As a key contributor to our AI and ML initiatives, you will: Contribute to well-defined prototype efforts and deliver production-ready features with high-quality code, tests, and CI/CD practices. Build core components for Agentic AI systems including RAG, embeddings, vector search, and tool/function calling, with guidance from senior engineers. Enhance model evaluation frameworks (offline/online, golden sets, HIL), monitor key metrics (quality, latency, cost, safety), and drive data-informed improvements. Collaborate on data ingestion, contracts, and catalog usage, ensuring compliance with privacy and access policies. Implement observability tools, guardrails, and cost controls; follow secure coding and Responsible AI practices for safety and auditability. Work cross-functionally with product, design, and platform teams; contribute to agile processes, documentation, and peer reviews. All About You
BS/MS in Computer Science, Data Science, or equivalent practical experience. Proficient in Python, REST, SQL, Git, Docker, and CI/CD workflows. Familiarity with LLMs, prompting, embeddings, RAG, and ML tools like PyTorch/TensorFlow. Exposure to major cloud platforms (Azure, AWS, GCP), data lakes/warehouses, and event-driven systems (e.g., Spark, Kafka). Strong coding practices, iterative development mindset, and clear written/verbal communication. Professional hands-on experience building services, ML features, or GenAI applications. Hands-on with Agentic AI frameworks, prompt management, and evaluation tooling. Understanding of Responsible AI and safety/guardrail systems. Knowledge of Cloudera AI, Databricks, Spark, Delta/Unity Catalog, or similar stacks. Portfolio of open-source contributions, hackathons, or published work. Job Posting Window
Applications for this job posting will be accepted on an ongoing basis.
#J-18808-Ljbffr