Top AI & Machine Learning Jobs in Dublin

Lead design, build, and operate scalable data pipelines and data products for foundation-model training, inference, and evaluation. Ensure data quality, lineage, governance, and performance; enable feature engineering and training datasets; collaborate with AI, platform, and product teams; mentor engineers and oversee delivery.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Ensure data quality, lineage, governance, and performance across batch and streaming workloads; enable feature engineering and feature stores; mentor engineers and drive delivery with platform and product teams.

Lead design, build, and operate scalable data pipelines and products for AI model training, inference, and experimentation. Ensure data quality, lineage, governance, and performance; enable feature engineering and feature stores; collaborate with AI, platform, and product teams; mentor engineers and oversee delivery.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Ensure data quality, governance, lineage, and secure access. Partner with AI, platform, and product teams, drive best practices, conduct reviews, mentor engineers, and manage delivery risks for AI data needs.

Leads technology and architecture for new business opportunities, evaluating feasibility, risks, build-versus-buy pathways, and scalable target architectures. Designs and guides AI-enabled and agentic systems, including workflows, orchestration, evaluation frameworks, and intelligence platforms. Partners with product, business, sourcing, and engineering teams, mentors technical talent, establishes engineering standards, and ensures solutions meet security, reliability, compliance, and performance requirements.

Provides senior technology and architecture leadership for new business opportunities. Evaluates technical feasibility, risks, build-versus-buy pathways, and target-state architectures. Designs and guides AI-enabled and agentic systems, platforms, workflows, and data-intensive applications through incubation and scaling. Partners with product, business, sourcing, and engineering teams while mentoring technical staff and ensuring secure, reliable, compliant, and scalable solutions.

Leads technology and architecture for new business opportunities, evaluating feasibility, risks, build-versus-buy decisions, and scalable target architectures. Partners with product, business, sourcing, and engineering teams to incubate and commercialize AI-enabled solutions. Designs agentic workflows, platforms, and distributed systems; ensures security, reliability, compliance, and performance; establishes reusable engineering capabilities; and mentors technical teams and cross-functional partners.

Serves as a senior technology and architecture leader for new business opportunities. Evaluates technical feasibility, emerging technologies, architecture, risks, and build-versus-buy decisions. Designs and guides AI-enabled and agentic systems through incubation, prototyping, commercialization, and scale. Establishes reusable platforms and architectural patterns while ensuring security, reliability, compliance, and scalability. Partners with product, business, sourcing, and engineering teams, and mentors technical staff across complex, ambiguous initiatives.

Leads technology strategy and architecture for new business opportunities involving AI, agentic systems, data platforms, and distributed software. Evaluates build, partner, invest, acquire, or discontinue options; guides solutions from incubation through scale; identifies reusable architectures and capabilities; assesses technical risks; and influences engineering standards. Partners with product, business, sourcing, and engineering teams while mentoring technical professionals and ensuring security, reliability, compliance, and scalability.

Provides senior technology and architecture leadership for new business opportunities involving AI, agentic systems, distributed software, and data-intensive platforms. Evaluates technical feasibility, risks, build-versus-buy options, architecture, scalability, security, and reliability across incubation and commercialization phases. Partners with product, business, sourcing, and engineering teams, mentors technical staff, and guides reusable platforms, engineering standards, and production-ready AI solutions.