Find Lead program security engineer Jobs in Clondalkin, D

AI Engineer 2
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Mastercard —Dublin, County Dublin
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AECOM —Dublin, County Dublin
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AI Engineer 2

Mastercard -
Dublin, County Dublin

Apply Now

Job details

Full-time
3 days ago

Qualifications

TensorFlow
CI/CD
Data modelling
Azure
Computer Science
Data structures
Google Cloud Platform
AWS
Analysis skills
Bachelor's degree
AI
Communication skills
Python

Full job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

AI Engineer 2

Overview
Mastercard is seeking an AI Engineer II to support the development and deployment of AI solutions that power strategic initiatives within the AI & Data organization. This role provides an opportunity to work on advanced AI technologies, including transformer-based and generative AI models, while contributing to the delivery of scalable, production-ready solutions.
Working closely with Senior, Lead, and Principal AI Engineers, you will help develop, evaluate, and operationalize AI capabilities that address real business challenges. This is a hands-on engineering role focused on building technical expertise, delivering high-quality solutions, and growing into greater levels of ownership and technical leadership.

Role
In this role, you will contribute to the development, testing, and deployment of AI and machine learning solutions across the program.
Key responsibilities include:

Develop and support AI and machine learning models under the guidance of senior team members
Contribute to the development and evaluation of transformer-based and generative AI solutions, including embeddings, tokenization, fine-tuning, and inference workflows
Build and maintain components of data preparation, feature engineering, and model training pipelines
Assist in creating and managing datasets required for model training, validation, and evaluation
Support the implementation and optimization of machine learning workflows and model-serving solutions
Help integrate AI models into applications, APIs, and production environments
Support model testing, validation, monitoring, and performance analysis to ensure quality and reliability
Apply established software engineering and MLOps best practices, including version control, testing, documentation, and deployment automation
Collaborate with AI engineers, data engineers, software engineers, and product teams to implement AI solutions
Troubleshoot issues related to model performance, data quality, and system functionality
Participate in code reviews, technical discussions, and knowledge-sharing activities
Stay current with emerging AI technologies, frameworks, and engineering best practices

All About You

2–5 years of experience in AI engineering, machine learning engineering, data science, software engineering, or a related technical field
Strong programming skills in Python
Experience using AI/ML frameworks such as PyTorch, TensorFlow, or similar technologies
Foundational understanding of machine learning, deep learning, and AI engineering concepts
Familiarity with transformer architectures, large language models, tokenization techniques, embeddings, and generative AI technologies
Experience working with data processing, feature engineering, and model training workflows
Familiarity with model evaluation techniques and performance measurement
Exposure to cloud-based development environments such as AWS, Azure, or GCP
Understanding of software engineering fundamentals, including testing, version control, CI/CD principles, and code quality practices
Familiarity with APIs and integrating machine learning models into applications is a plus
Knowledge of data structures, algorithms, and scalable computing concepts
Strong analytical and problem-solving skills
Effective communication and collaboration skills, with the ability to work in a cross-functional team environment
Demonstrated ability to learn new technologies quickly and adapt to evolving technical requirements
Bachelor's degree or equivalent practical experience in Computer Science, Engineering, Data Science, Mathematics, or a related field

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.

Apply Now

Refine Your Search

lead program security engineer jobs in clondalkin, d

AI Engineer 2

Databricks Solution Architect – Financial Crime & Banking

Tech Infrastructure Program Manager , Data Centre Delivery

Technology Operational Readiness Lead – Drug Product Manufacturing

Manager, Software Development, AWS In-Memory Databases

Partner Technical Architect - Agentforce

Software Engineer – SoC FPGA

Software Development Manager, AWS Databases, RDS Platform

Senior Embedded Systems Design Engineer

Director of Software Engineering

Principal Software Engineer, Amazon DynamoDB

Senior Cloud Engineer (m/f/x)*

Manager, Software Engineering

Director of AI Engineering

Senior Success Architect- Health and life Sciences Industry

Design & Engineering Manager (Electrical - Data Centres) - Dublin

Senior Manager, Architecture & Components

Software Development Manager, ICON

Principal Engineer, Design Verification Engineering

Associate Electrical Director: Data Centres

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