Top Tech Jobs & Startup Jobs in Dublin

Develop and deploy production machine learning solutions for forecasting, recommendations, propensity modeling, fraud detection, risk modeling, and customer analytics. Define experimentation and evaluation frameworks, apply embeddings and foundation models, measure business impact, and partner with product, engineering, analytics, and business teams. The role also contributes to reusable AI standards and mentors junior data scientists.

Leads complex, cross-functional technical programs across engineering teams, regions, architectures, and external vendors. Establishes program governance, delivery processes, operating rhythms, reporting, and scalable collaboration models. Manages risks, escalations, stakeholder alignment, and executive communications while driving predictable delivery and supporting the growth of distributed engineering squads.

Lead complex, cross-functional technical programs from strategy through delivery. Establish program governance, delivery processes, and operating rhythms; coordinate engineering teams, regions, vendors, and stakeholders; manage escalations, risks, dependencies, and executive communications; and improve scalable delivery models for a growing global engineering organization. The role requires independent execution in ambiguous environments, strong agile and scrum expertise, and the ability to align teams toward predictable outcomes.

Lead complex, cross-functional technical programs across engineering teams, regions, vendors, and organizational domains. Establish program governance, delivery processes, operating rhythms, and scalable collaboration models. Manage risks, escalations, dependencies, reporting, and stakeholder alignment while communicating status and decisions to senior leadership. Support the scaling and onboarding of engineering squads and drive predictable delivery in ambiguous, evolving environments.

Develop and deploy production machine learning solutions for forecasting, recommendation, propensity modeling, fraud detection, risk modeling, and customer analytics. Define experimentation methods, evaluation frameworks, and success metrics; apply foundation-model embeddings and modern ML techniques; measure business impact; and collaborate with product, engineering, analytics, and business teams. Communicate technical findings, establish modeling standards, create reusable assets, and mentor junior data scientists.

Leads complex, cross-functional technical programs across engineering teams, regions, vendors, and organizational domains. Establishes program governance, delivery processes, operating rhythms, and scalable collaboration models. Manages risks, escalations, stakeholder alignment, reporting, and accountability while communicating program status and decisions to senior leadership. Supports the growth of engineering squads and drives predictable delivery in ambiguous, fast-evolving environments.

Build and operate highly available, scalable Linux production platforms across public clouds. Develop infrastructure-as-code, automation, deployment tooling, monitoring, and security controls using Kubernetes and CI/CD technologies. Troubleshoot infrastructure, networking, performance, and availability issues; support engineering teams; maintain documentation; and participate in on-call rotations. The role requires cloud, container orchestration, Linux systems, programming, database, networking, and infrastructure automation expertise.

Develop and deploy production machine learning solutions for forecasting, recommendation, propensity modeling, fraud detection, risk modeling, and customer analytics. Define modeling and experimentation strategies, apply foundation-model embeddings, create evaluation frameworks, measure business impact, and collaborate with product, engineering, analytics, and business teams. The role also involves communicating technical insights, establishing modeling standards, developing reusable assets, and mentoring junior data scientists.

Build and operate highly available, scalable cloud infrastructure for Ekata. Develop infrastructure-as-code, automation, deployment tooling, monitoring, and security controls across AWS, Azure, and GCP. Manage Kubernetes and Linux systems, troubleshoot networking and production issues, improve reliability and performance, maintain documentation, support engineering teams, and participate in on-call rotations. Develop custom tools using Go, Python, Rust, or Bash while ensuring best practices and secure system integration.

Build and operate highly available, scalable cloud platforms for Ekata. Responsibilities include managing Linux production systems, infrastructure as code, CI/CD, Kubernetes, cloud services, monitoring, security, networking, automation, troubleshooting, documentation, and on-call support. The role also develops tooling in Go, Python, Rust, or Bash and helps engineering teams improve deployment reliability, system performance, and service availability.