Top AI Jobs in Dublin

Lead architecture and deliver cloud-native workplace solutions, engage stakeholders, define target-state architectures, integrate enterprise AI safely, produce and review secure production code, drive resiliency and automation, and evaluate vendor technologies.

Lead development and adoption of Medical Insights capabilities across Medical Affairs, applying advanced analytics and AI to translate medical data into actionable insights. Drive strategy, governance, use-case prioritization, tool requirements, stakeholder alignment, value measurement, and adoption to inform evidence generation, medical strategy, and decision-making across cross‑functional and global teams.

Senior AI Engineer to design, build, and operate production-grade AI and agentic systems. Responsibilities include model serving, monitoring, retraining, pipelines, APIs, feature engineering, partnering with data scientists, and ensuring reliability, security, and governance of AI solutions.

Build, deploy, and operate production-grade AI and agentic systems. Implement model serving, monitoring, evaluation, and retraining. Partner with data scientists to productionise models, contribute to data preparation and feature engineering, and ensure solutions meet performance, reliability, security, and governance standards.

Senior individual contributor building and operating production-grade AI and agentic systems. Responsibilities include designing, deploying, and monitoring ML services, pipelines and APIs; productionising models with data scientists; ensuring reliability, security, and governance; and collaborating with platform, security, and infrastructure teams.

Build, deploy, and operate production-grade AI and agentic systems. Implement model serving, monitoring, evaluation, retraining, pipelines and APIs. Partner with data scientists to productionize models, contribute to data preparation and feature engineering, participate in design reviews, and ensure solutions meet security, reliability, and governance standards.

Build, deploy, and operate production-grade AI and agentic systems. Implement model serving, monitoring, evaluation and retraining. Partner with data scientists to productionize models, contribute to data preparation and feature engineering, and ensure solutions meet performance, security and governance standards while collaborating across platform and infrastructure teams.

Build and operate production-grade AI and agentic systems across the full lifecycle: design, model serving, pipelines, monitoring, retraining, and APIs. Partner with data scientists and platform teams to productionize models, ensure security, reliability, and governance, and participate in design reviews and knowledge sharing.

Build, deploy, and operate production-grade AI and agentic systems. Implement model serving, monitoring, evaluation, and retraining pipelines. Partner with data scientists to productionize models, contribute to feature engineering and data preparation, participate in design reviews, and ensure performance, reliability, security, and governance across AI solutions.

Senior individual contributor building and operating production-grade AI and agentic systems. Responsibilities include model serving, pipelines, monitoring, retraining, feature engineering, partnering with data scientists to productionize models, and ensuring performance, reliability, security and governance at scale.

Build, productionize and operate AI and agentic systems across the full lifecycle. Implement model serving, monitoring, evaluation, and retraining; develop ML services, pipelines and APIs; collaborate with data scientists, platform, security and infrastructure teams to deliver secure, scalable production AI solutions.

Build, deploy, and operate production-grade AI and agentic systems. Implement model serving, monitoring, evaluation, and retraining pipelines; partner with data scientists to productionize models; contribute to data preparation and feature engineering; ensure performance, reliability, security, and governance; and collaborate across platform, security, and infrastructure teams.

Build, deploy, and operate production-grade AI and agentic systems. Develop ML services, pipelines, model serving, monitoring, evaluation, and retraining. Partner with data scientists to productionize models, contribute to data preparation and feature engineering, participate in technical design reviews, and ensure solutions meet performance, security, reliability, and governance standards.

Lead development and deployment of scalable AI/ML solutions, translate stakeholder needs into technical designs, oversee data preparation and model performance, mentor engineers, and deliver productionized models including advanced transformer and generative AI applications.

Lead AI initiatives: architect and deploy scalable ML systems, translate stakeholder needs into AI solutions, oversee data integration and model performance, deliver AI-driven insights, and mentor engineers and data scientists.

Lead design, development, and deployment of scalable AI/ML solutions. Translate stakeholder needs into models, oversee data preparation, mentor engineers, deliver production systems, and conduct performance reviews.

Lead development and delivery of scalable AI/ML solutions, translate stakeholder needs into technical designs, oversee data integration and model deployment, mentor and review junior engineers, and manage performance and post-implementation reviews.

Lead and deliver end-to-end AI/ML solutions: design, build, deploy, and tune models; integrate and prepare data; translate stakeholder needs to technical solutions; mentor and review junior engineers; manage project timelines, budgets, and post-implementation reviews.

Lead development and deployment of scalable AI/ML solutions, translate stakeholder needs into technical designs, oversee data integration and model performance, mentor engineers, and deliver production AI systems and visualizations on time and on budget.

Lead development and deployment of scalable AI/ML solutions; architect models and data pipelines; mentor engineers and data scientists; translate stakeholder needs to technical designs; ensure model performance, integration, and post-implementation reviews.

Lead development and deployment of advanced AI/ML solutions. Architect scalable ML systems, mentor engineers, translate stakeholder needs into technical designs, oversee data preparation, model deployment, performance tuning, and deliver measurable business impact.

Lead AI Engineer to design, develop, and deploy scalable AI/ML solutions. Lead projects from concept to production, supervise data integration and model performance, mentor engineers, and present outcomes to stakeholders. Work includes advanced ML, deep learning, NLP, generative AI, and MLOps.

Lead development and deployment of scalable AI/ML solutions. Translate stakeholder needs into technical designs, oversee data preparation, model development, deployment, performance tuning, and mentor engineers and data scientists.

The Lead AI Engineer will develop advanced AI solutions, mentor a team, and oversee machine learning initiatives, ensuring data readiness and translating stakeholder needs into AI-driven solutions.

The role involves applying advanced analytics in healthcare, developing coding solutions, collaborating with teams, and mentoring. Focus is on data science and improving healthcare outcomes.