Top Tech Jobs & Startup Jobs in Dublin

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps (tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams, perform model tuning and troubleshooting, and follow security and engineering standards.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, inference, and MLOps practices. Collaborate with product, data, and engineering teams, perform model evaluation and tuning, and ensure production reliability and monitoring.

Build, test, and deploy AI/ML solutions including transformer-based and generative models. Support data preparation, feature engineering, training pipelines, model serving, monitoring, and integration into applications while following MLOps and software engineering best practices.

Design, build, and operationalize transformer-based and generative AI models; develop training and inference workflows, data pipelines, and MLOps practices; deploy and monitor models in production; collaborate with product and engineering teams.

Contribute to development, testing, and deployment of transformer-based and generative AI models. Build data preparation, feature engineering, training pipelines, and model-serving solutions. Support evaluation, monitoring, integration into applications/APIs, and apply MLOps and software engineering best practices while collaborating across cross-functional teams.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, training workflows, model serving/inference, and MLOps practices. Collaborate with product, data, and engineering teams to integrate models into applications, run evaluations, troubleshooting, and performance tuning while following engineering standards.

Build, operate, and automate cloud infrastructure and CI/CD pipelines to enable foundation model development and production AI workloads. Manage model deployment (inference, batch, streaming), ensure observability, resilience, security (secrets management, IAM), and collaborate with AI, data, and software engineers to streamline development-to-production workflows and incident response.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product, data, and engineering teams to operationalize and monitor model performance.

Design, develop, and productionize transformer-based and generative AI models. Build training workflows, data pipelines, feature engineering, model serving, and MLOps practices. Collaborate with product, data, and engineering teams, perform code reviews, troubleshoot and optimize models in production, and maintain model lifecycle and monitoring.

Lead lifecycle operations for enterprise load balancer platforms: administer, monitor, patch, back up PKI, troubleshoot complex network/application traffic, automate deployments and monitoring, train operations teams, and collaborate on scalable end-to-end network/application architectures to meet availability and security standards.