Top AI & Machine Learning Jobs in Dublin

Design and deliver enterprise-grade AI solutions using LLMs, RAG, and vector search. Build knowledge bases, integrate models via MCP/LangChain, develop APIs and microservices, and architect scalable, secure cloud systems on AWS/Cloudera/Databricks. Collaborate cross-functionally, monitor model performance in production, ensure compliance and data governance, and mentor junior engineers.

Lead engineering teams building API platforms and backend services to expose foundation model capabilities. Own architecture, security, reliability, CI/CD, observability, and model integration. Manage multiple workstreams, hire and coach engineers, define technical roadmaps, and ensure production readiness and governance for scalable AI services.

Lead engineering for production-grade agentic AI products and reusable agent frameworks. Drive architecture, platform capabilities (lifecycle, retrieval, observability, safety), team scaling, AI tooling adoption, and cross-functional delivery to turn experiments into secure, scalable enterprise solutions.

Design, build, and deploy production AI/ML solutions including transformer and generative models. Implement data pipelines, feature engineering, training workflows, model serving, and MLOps practices. Collaborate with product and engineering teams, participate in code reviews, troubleshoot and optimize models in production.

Design, build, and deploy production AI/ML solutions, focusing on transformer and generative models. Develop data pipelines, training workflows, model serving, and MLOps practices. Collaborate with product, data, and engineering teams to ensure reliable, monitored, high-quality model performance.

Design, build, and deploy production AI solutions including transformer-based and generative models. Build data pipelines, training workflows, model serving and inference, apply MLOps practices, collaborate with product and engineering teams, and monitor and tune models in production.

Design, build, and deploy production-quality AI solutions. Develop and optimize transformer and generative models, manage data pipelines and training workflows, implement model serving and MLOps practices, and collaborate with product and engineering teams to operationalize and monitor AI systems.

Design, build, and deploy production AI solutions including transformer and generative models; develop data pipelines and feature engineering; implement model serving, monitoring, and MLOps practices; collaborate with product and engineering teams to ensure reliable, performant systems.

Design, build, and deploy transformer-based and generative AI models into production. Build data pipelines and feature engineering, implement model serving and inference, apply MLOps practices (tracking, versioning, testing, monitoring), collaborate with product and engineering teams, and troubleshoot and optimize model performance in production.

Design, build, and deploy production AI/ML solutions including transformer and generative models. Develop data pipelines, training workflows, model serving, and MLOps practices. Collaborate with product and engineering teams, perform evaluation and performance tuning, and ensure maintainable, production-grade AI systems.