Top AI Jobs in Dublin

Designs, develops, tests, and supports Java-based cloud-native applications on Google Cloud Platform. Builds REST APIs, integrates AI services, applies secure coding practices, contributes to CI/CD and deployment automation, and implements observability through logging, metrics, dashboards, and alerts. Troubleshoots production issues, performs root-cause analysis, participates in architecture discussions and code reviews, collaborates across engineering and business teams, and mentors junior developers.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.

The AI Inference Engineer optimizes Large Language Models for inference in diverse environments, ensuring high performance and reliability through optimized deployment, hardware acceleration, and scalable architecture.

Lead AI-driven resilience assurance initiatives, utilizing predictive analytics and real-time monitoring to enhance compliance and organizational resilience. Develop autonomous systems for continuous audits and dynamic maturity assessments, translating insights into actionable strategies for stakeholders.

Lead and mentor a team of Applied Scientists and AI/ML Engineers to design, build, and deploy production-grade AI features for an AI-native CRM. Drive technical strategy for LLM operations, agentic workflows, RAG/vector-based solutions, and scalable data pipelines while partnering with platform teams to ensure performant, customer-centric ML systems.

Lead Moonshot's applied AI safety portfolio, directing red teaming, adversarial evaluation, and methodological standards across online harms. Advise AI companies and regulators, manage client relationships and staff, develop offerings and funding, and ensure ethical, documented delivery of safety evaluations and interventions for violence, CSEA, mental-health, and child/teen risks.

Lead design and governance of ICON's end-to-end AI platform, multi-agent frameworks, and supporting services. Define cloud-native, scalable architectures, integration patterns, APIs, and standards; lead solution architecture, design reviews, and mentor engineering teams to deliver secure, high-performing AI/ML production systems.

Lead the architecture and implementation of a production-grade generative AI media platform. Build reproducible, versioned pipelines, train LoRAs, integrate control techniques (ControlNet, IP-Adapter, inpainting), automate QC against product references, deploy internal tools, and partner with design to own the technical roadmap and enable creative teams.

Seeking a Senior Full-Stack Engineer to develop AI-driven web and mobile applications, focusing on scalable architectures and API integrations. Collaborate with product teams to translate features into technical solutions.

Manage multilingual data collection and Large Language Model evaluation projects, ensuring quality assurance and effective global team coordination.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Lead end-to-end technical projects for a Voice AI CX platform: scope, plan, manage releases, align product to customer requirements, track metrics, ensure quality, and communicate status to clients and engineering.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Build and ship secure, production-ready CI/CD and AI-integrated features end-to-end. Design, implement, and iterate on products (e.g., hardened GitHub Actions, agent features), work closely with Product and front-end teams, make architectural decisions, and extend Chainguard's agentic AI capabilities into customer-facing experiences.

Build, run, and improve AI-driven automations for FP&A, tax, and finance operations. Connect ERP, spend, equity, HRIS, and CRM systems to LLM-powered agents, maintain auditable workflows, and expand the finance team's AI capabilities while supporting forecasting, budgeting, reporting, and month-end close.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

Support AI and machine learning initiatives through data collection, cleaning, transformation, analysis, ETL pipeline development, feature engineering, basic model development, dashboards, reporting, documentation, and SQL and cloud learning under senior mentorship.

Join a project evaluating AI chatbot voice mode by conducting voice conversations in Irish (en_IE), following predefined prompts and goals, then rating interactions and completing evaluations in English. Work remotely on personal smartphone and laptop, follow confidentiality and project guidelines, and be prepared for variable workloads and environment conditions.

Design and implement AI-powered internal tools for GTM use cases, managing full lifecycle from data modeling to production. Collaborate closely with GTM teams to translate data into actionable insights with a focus on measurable business impact.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Lead hands-on applied AI work: prototype demos, accelerate customer POC-to-production, perform technical onboarding, optimize distributed training and inference on GPU infrastructure, research and implement emerging ML techniques, and feed actionable product feedback while producing reusable assets and benchmarks.