Top Tech Jobs & Startup Jobs in Dublin

Design, build, and productionize transformer-based and generative AI models. Develop training and inference pipelines, integrate models into APIs, apply MLOps practices, monitor performance, and collaborate with product and engineering teams to deliver reliable AI solutions.

Lead daily administration, monitoring, patching and troubleshooting of enterprise load balancers. Ensure configurations, PKI, and monitoring meet availability and security standards; automate builds and diagnostics; collaborate with engineering and delivery teams to design scalable application architecture and train operations staff.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, model serving, and inference APIs. Apply MLOps practices (tracking, versioning, testing, monitoring), collaborate with product and engineering teams, troubleshoot and optimize production models, and follow security and engineering standards.

Develop, evaluate, and deploy transformer-based and generative AI models. Build data preparation, feature engineering, training pipelines, and model-serving solutions. Support testing, monitoring, performance analysis, and integration of AI into applications using MLOps and software engineering best practices while collaborating with cross-functional teams.

Manage, monitor, patch, and troubleshoot load balancer appliances and configurations to ensure high availability. Design monitoring and automation, resolve complex network/application traffic issues, support multi-cloud deployments, collaborate with engineering and operations, lead incident troubleshooting, and provide training and technical documentation.

Lead DevOps Engineer responsible for building and operating CI/CD pipelines, cloud infrastructure (primarily AWS), and runtime environments to deploy and operate foundation models and data workflows. Automate deployments, ensure observability, embed security best practices, support Databricks, troubleshoot production incidents, and promote DevOps/IaC practices to enable scalable, reliable AI systems.

Lead engineering and contribute to design, development, and maintenance of high-performance, high-volume Java applications supporting virtual commercial payments. Collaborate with product and tech leads to define features, deliver secure cloud-native solutions, mentor team members, and ensure SLAs, quality, and continuous process improvements.

Lead development of high-performance, high-volume Java applications for commercial virtual payments. Define features with product and tech leads, maintain SLAs, provide technical mentorship, improve processes, and contribute to cloud-native REST/SOAP API solutions.

Build and operate scalable CI/CD pipelines, cloud infrastructure, and runtime environments to deploy and operate foundation models and AI/data workloads; automate releases, ensure observability, security, and high availability; support Databricks, incident response, and cross-team collaboration to move AI solutions from development to production.

Design, build, and productionize transformer-based and generative AI models. Develop training workflows, data pipelines, feature engineering, model serving, and inference APIs. Apply MLOps best practices (experiment tracking, versioning, testing, monitoring). Collaborate with product, data, and engineering teams to translate requirements, perform performance tuning, and maintain production model reliability.