Top AI & Machine Learning Jobs in Dublin

Provides senior technology and architecture leadership for AI-enabled business opportunities. Evaluates technical feasibility, risks, build-versus-buy options, and target architectures; guides prototypes through commercialization and scale. Designs agentic AI workflows, platforms, and reusable capabilities while ensuring security, reliability, compliance, and performance. Partners with product, business, sourcing, and engineering teams, influences architectural decisions, and mentors technical stakeholders.

Provides senior technology and architecture leadership for AI-enabled business opportunities. Evaluates technical feasibility, risks, architecture, and build-versus-buy decisions; guides solutions through incubation, commercialization, and scale. Designs agentic AI workflows, platforms, and reusable capabilities while ensuring security, reliability, compliance, and performance. Partners with product, business, sourcing, and engineering teams, and mentors technical staff. Builds production-grade distributed software and data-driven systems using backend, cloud, data processing, and AI technologies.

Leads technology strategy and architecture for new AI-enabled business opportunities. Evaluates technical feasibility, risks, build-versus-buy pathways, and target-state architectures. Guides agentic AI, platform, integration, security, reliability, and scalability decisions from incubation through commercialization. Partners with product, business, sourcing, and engineering teams; defines reusable capabilities; and mentors engineers and architects. Requires extensive distributed software engineering, data-intensive application, cloud, AI, and enterprise architecture experience.

Serves as the senior technology and architecture advisor for new business opportunities. Partners with product, business, sourcing, and engineering teams to assess feasibility, shape AI-enabled solutions, evaluate build-versus-buy paths, identify technical risks, and guide architecture from incubation through scale. Designs agentic workflows and intelligence systems, defines reusable platforms and target architectures, ensures security and reliability standards, and mentors engineers and cross-functional partners.

Serve as the principal technology and architecture advisor for new business opportunities. Evaluate technical feasibility, risks, platforms, and build-versus-buy decisions; guide AI-enabled and agentic system design; shape architectures through incubation and commercialization; and establish reusable capabilities and engineering standards. Partner with product, business, sourcing, and engineering teams while mentoring technical professionals and ensuring secure, reliable, scalable production systems.

Leads the design, development, deployment, and evaluation of machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, and partners with product, engineering, analytics, and business teams. Mentors data scientists and AI engineers, presents technical recommendations to leadership, supports hiring, and shapes the organization’s long-term technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, measures business impact, partners with cross-functional stakeholders, presents findings to leadership, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the long-term technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model representations, measures business impact, and partners with cross-functional stakeholders. Mentors data scientists and AI engineers, presents recommendations to leadership, contributes to hiring, and helps shape the organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies embeddings and foundation models, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. Contributes to hiring, capability development, and the long-term technical direction of the AI organization.