Top Tech Jobs & Startup Jobs in Dublin

Develop, test, and deploy AI/ML solutions including transformer and generative models. Build data preparation, feature engineering, training pipelines, integrate models into production, support evaluation, monitoring, and MLOps best practices while collaborating across engineering and product teams.

Lead global engineering teams to define and execute the Commercial Acceptance technology roadmap. Drive large-scale technology transformation, ensure operational stability, improve platform metrics, collaborate with product and enterprise leaders, and grow technical talent across multiple regions while embedding Mastercard principles.

Develop, evaluate, and deploy transformer-based and generative AI models. Build data preparation, feature engineering, training pipelines, and model-serving solutions. Support testing, monitoring, performance analysis, and integration of AI into applications using MLOps and software engineering best practices while collaborating with cross-functional teams.

Build, test, and deploy AI/ML solutions including transformer-based and generative models. Support data preparation, feature engineering, model training, evaluation, serving, monitoring, and integration into applications and APIs. Apply software engineering and MLOps best practices, collaborate across teams, troubleshoot performance and data issues, and contribute to production-ready, scalable AI capabilities.

Contribute to development, testing, and deployment of transformer-based and generative AI models. Build data preparation, feature engineering, training pipelines, and model-serving solutions. Support integration into applications/APIs, monitoring, validation, and MLOps practices while collaborating with cross-functional teams and applying software engineering best practices.

Develop, test, and deploy AI/ML solutions including transformer-based and generative models. Build data preparation, feature engineering, training pipelines, and model-serving solutions. Support evaluation, monitoring, integration into applications/APIs, and follow MLOps and software engineering best practices while collaborating with cross-functional teams.

Build, test, and deploy transformer-based and generative AI models. Support data preparation, feature engineering, training pipelines, model serving, evaluation, monitoring, and integration into applications using MLOps and software engineering best practices.

Develop, evaluate, and deploy transformer-based and generative AI models and pipelines. Build data preparation, feature engineering, training, inference, and model-serving components, apply MLOps and software engineering best practices, integrate models into applications/APIs, monitor performance, and collaborate across cross-functional teams.

Lead development of high-performance, Java-based fraud and identity decisioning platform. Own full SDLC, design scalable solutions, enforce best practices, mentor engineers, troubleshoot production incidents, run PoCs, and collaborate with architects, product owners and vendors to meet SLAs and security/PCI standards.

Lead a team to design, develop, and maintain high-performance, Java-based fraud detection and identity services. Own full SDLC artifacts, performance testing, deployments, automation, mentoring, incident troubleshooting, PoCs, vendor integration, and compliance with Mastercard/PCI standards within an Agile SCRUM environment.