Back to Search Results
Get alerts for jobs like this Get jobs like this tweeted to you
Company: Mastercard
Location: Dublin, Ireland
Career Level: Associate
Industries: Banking, Insurance, Financial Services

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

Lead Machine Learning Engineer Overview:
We are seeking a highly skilled and forward-thinking Machine Learning Engineer to lead the development and deployment of scalable machine learning systems that drive innovation and deliver measurable impact across the business. This role involves building robust ML pipelines, optimizing model performance, and collaborating with cross-functional teams to integrate intelligent solutions into production environments. The ideal candidate combines deep technical expertise with strong engineering discipline and a passion for solving real-world problems.

Role:
Responsible for developing machine learning–driven analytical solutions and identifying opportunities to support business and client needs in a scalable and automated manner, facilitating informed recommendations and decisions. Activities include designing and deploying ML models, building end-to-end pipelines, conducting performance analyses, ad hoc reporting, and developing ML-powered data visualizations.

In this position, you will:
Lead complex initiatives and projects to build and deploy ML systems that solve critical business questions and automate decision-making processes
Translate client/stakeholder needs into machine learning solutions in collaboration with internal and external partners and present findings and outcomes to clients/stakeholders
Identify rich data sources and oversee the integration, cleaning, and transformation of datasets to ensure consistency and readiness for ML applications
Deliver high-quality ML solutions and tools within agreed-upon timelines and budget parameters and conduct post-implementation reviews
Guide others to develop sophisticated ML models and engineering solutions (e.g., recommendation systems, anomaly detection engines, predictive maintenance tools) utilizing supervised, unsupervised, and reinforcement learning techniques
Delegate and review work for junior-level colleagues to ensure downstream applications and tools are not compromised or delayed
Serve as a technical coach for junior-level colleagues and develop technical talent via ongoing technical training, peer review, and mentorship
All about you:
Proven experience designing, building, and deploying machine learning systems in production
Strong proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, PyTorch
Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes)
Solid understanding of ML algorithms, model evaluation, feature engineering, and data preprocessing
Experience with complex neural network architectures and transformer-based models (e.g., BERT, GPT, ViTs) is strongly preferred
Familiarity with MLOps practices including CI/CD, model monitoring, and automated retraining
Excellent communication and stakeholder management skills
Demonstrated ability to mentor and grow technical teams

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 on company website