Top AI & Machine Learning Jobs in Dublin

Lead the design, development, and production deployment of AI-powered products, intelligent agents, and cloud-native analytics platforms. Architect agentic systems with reasoning, memory, retrieval, evaluation, safety, and human-in-the-loop controls. Build scalable services, APIs, and data applications using AWS, Azure, Databricks, Spark, Python, and Java. Drive architecture reviews, engineering excellence, CI/CD, DevSecOps, technical execution, modernization, and mentorship across globally distributed teams.

Lead the architecture and development of scalable, cloud-native AI products, intelligent agents, agentic workflows, and analytics platforms. Design production-grade systems using LLMs, retrieval, orchestration, memory, evaluation, and safety controls. Build APIs and distributed services with Python, Java, AWS, Azure, Databricks, and Spark. Drive technical execution, architecture reviews, DevSecOps, automation, reliability, governance, and mentoring across globally distributed engineering teams.

Build and lead scalable full-stack, data-intensive applications using distributed systems, cloud technologies, Databricks, Spark, and AI agentic workflows. Responsibilities include system design, API and data architecture, performance optimization, troubleshooting, secure coding, testing, observability, CI/CD, production readiness, cross-functional collaboration, and mentoring engineers.

Lead design, build, and operate scalable data pipelines and products for foundation model training, inference, and evaluation. Own ingestion, transformation, batch/stream processing, feature engineering, data quality, lineage, governance, and performance tuning. Collaborate with AI, platform, and product teams to ensure production readiness, security, and observability. Provide technical leadership, code/design reviews, mentoring, and delivery planning across the program.

Lead design, build, and operate scalable data pipelines and products to support foundation models and AI workloads. Own ingestion, transformation, feature engineering enablement, data quality, governance, and production readiness while mentoring engineers and ensuring enterprise standards.

Lead design, build, and operate scalable data pipelines and products for AI foundation models. Own ingestion, batch and streaming transforms, feature engineering and training datasets, ensure data quality, lineage, governance, performance tuning, and secure access. Collaborate with AI, platform, and product teams, lead technical reviews, mentor engineers, and contribute to program planning and delivery.

Lead design, build, and operate scalable, governed data pipelines and products for AI model training, inference, and evaluation. Partner with AI engineers, ensure data quality, lineage, governance, and performance; mentor engineers and drive delivery.

Lead design, build, and operate scalable data pipelines and data products to support foundation model training, inference, and evaluation. Partner with AI and platform teams to enable feature engineering, ensure data quality, governance, lineage, and secure access. Drive best practices for modeling, partitioning, performance, monitoring, and CI/CD. Provide technical leadership, code/design reviews, mentoring, and program-level planning to ensure production-ready, reliable data for AI workloads.

Lead design, build, and operate scalable, governed data pipelines and products for foundation models and AI workloads. Partner with AI and platform teams to enable feature engineering, training/inference datasets, data quality, lineage, and secure access. Provide technical leadership, code/design reviews, mentoring, and delivery planning across cloud-native distributed data environments.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Own ingestion, transformation, streaming and batch patterns, feature engineering support, data quality, lineage, governance, and performance optimization. Collaborate with AI, platform, and product teams, lead technical reviews, mentor engineers, and contribute to program planning and delivery oversight.