Top Machine Learning Jobs in Dublin

Leads enterprise technical program management across Applied AI, data platforms, and UX engineering. Owns strategic initiatives from scoping through production and handoff, coordinating engineering, data science, product, design, architecture, security, and privacy teams. Establishes governance, integrated plans, risk tracking, executive communications, success metrics, and delivery practices. The role also supports program management talent development and improves operating models, tooling, agile practices, and capacity planning.

Leads a portfolio of enterprise technical programs across applied AI, data platforms, and UX engineering. Responsibilities include integrated planning, cross-functional alignment, governance, risk and dependency management, executive communications, success metrics, delivery-process improvement, capacity planning, and developing program management talent. The role requires strong technical fluency, enterprise-scale program leadership, stakeholder influence, strategic judgment, and familiarity with modern program management tools and methodologies.

Leads a portfolio of enterprise technical programs spanning AI, data platforms, and UX engineering. Establishes integrated plans, governance, risk tracking, executive communications, success metrics, and delivery processes. Partners with engineering, data science, product, design, architecture, security, privacy, and infrastructure teams to deliver complex initiatives from concept through production. Also supports program management talent development and improves operating models, tooling, agile practices, and capacity planning.

Leads a portfolio of enterprise technical programs across AI, data platforms, and UX engineering from planning through production handoff. Establishes governance, manages dependencies and risks, aligns engineering and business stakeholders, communicates with executives, defines success metrics, improves program-management practices, and supports program talent development. Requires strong technical fluency, enterprise-scale program leadership, strategic judgment, and expertise with modern planning tools and delivery methodologies.

Leads a portfolio of enterprise technical programs across AI, data platforms, and UX engineering from scoping through production and operational handoff. Establishes governance, integrated plans, risk tracking, executive reporting, success metrics, and delivery practices. Partners with engineering, data science, product, design, architecture, security, privacy, and infrastructure teams to resolve dependencies and deliver scalable outcomes. Also supports program management talent development and operating-model improvement.

Owns product strategy, roadmap, and feature definition for AI and data products. Partners with engineering, design, marketing, and leadership to prioritize initiatives, translate OKRs into delivery plans, define requirements, manage backlogs, and guide solution trade-offs. Uses customer research, operational data, and product analytics to drive product decisions, innovation, and measurable business value in a SaaS environment.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre demonstrations. Owns technical strategy, reusable frameworks, emerging technology integration, production delivery, operational support, and technical standards across AI, mixed reality, spatial computing, IoT, visualization, and interactive installations. Partners with product, engineering, creative, security, vendors, and executive stakeholders while translating customer and business needs into reliable, scalable experiences.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks for AI demonstrations, mixed reality, spatial computing, interactive installations, data visualization, and connected environments. Owns delivery from concept through production, establishes technical standards and operational models, and partners with engineering, product, creative, security, vendors, and executive stakeholders. The role also mentors teams and translates customer and business needs into reliable, scalable technology experiences.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks for AI demonstrations, mixed reality, spatial computing, interactive installations, visualization, IoT environments, and production systems. Owns delivery from concept through deployment, establishes technical standards and support models, and leads cross-functional teams and external partners. Engages executives and customers to translate business needs into compelling, reliable technology experiences while mentoring teams and driving adoption of emerging technologies.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks for AI demonstrations, mixed reality, spatial computing, interactive installations, visualization platforms, IoT environments, and executive showcases. Owns delivery from concept through production, establishes technical standards and support models, evaluates emerging technologies, and partners with product, engineering, creative, security, vendors, and senior stakeholders to create reliable customer-facing experiences.

Lead the global architecture, prototyping, engineering, and deployment of immersive Mastercard Experience Centre technologies. Develop scalable demonstrations involving AI, mixed reality, spatial computing, IoT, visualization, and interactive installations. Establish technical standards, reusable frameworks, deployment playbooks, and operational support models. Partner with product, engineering, creative, security, vendors, and executive stakeholders while mentoring teams and translating customer needs into reliable, compelling technology experiences.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Develops interactive demonstrations involving AI, mixed reality, spatial computing, visualisation, IoT, holography, and digital installations. Establishes reusable technical frameworks, deployment standards, and operational support models while managing end-to-end technical delivery. Partners with product, engineering, creative, security, vendors, and executive stakeholders to create reliable customer-facing experiences and translate innovation concepts into scalable production environments.

Leads the global architecture, prototyping, engineering, and deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks for AI demonstrations, mixed reality, spatial computing, interactive installations, IoT environments, and visualization platforms. Owns delivery from concept through production, establishes technical standards and support models, and collaborates with product, engineering, creative, security, vendors, and executive stakeholders. Translates customer and business needs into reliable, scalable technology experiences while mentoring teams and driving emerging-technology adoption.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks and production systems for AI, mixed reality, spatial computing, visualization, IoT, and interactive installations. Partners with product, engineering, creative, security, vendors, and executive stakeholders to deliver reliable customer-facing demonstrations, establish technical standards, mentor teams, and translate innovation concepts into scalable experiences.

Leads the architecture, prototyping, engineering, and global deployment of immersive Mastercard Experience Centre technologies. Designs reusable frameworks and production systems for AI, mixed reality, spatial computing, interactive installations, visualization, IoT, and executive demonstrations. Oversees technical strategy, delivery, integrations, operational support, and global rollout while partnering with product, engineering, creative, security, vendors, and senior stakeholders. Translates customer and business needs into scalable, reliable, and compelling technology experiences.

Leads EMEA and LATAM international tax accounting, quarterly US GAAP tax provisions, Pillar 2 calculations, tax compliance, audits, statutory reporting, and tax planning. Partners with legal, accounting, FP&A, and external advisors while driving AI automation, tax technology, process improvements, SOX controls, legislation research, and business-critical international tax projects.

Leads the design, development, deployment, and evaluation of machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, and partners with product, engineering, analytics, and business teams. Mentors data scientists and AI engineers, presents technical recommendations to leadership, supports hiring, and shapes the organization’s long-term technical direction.

Lead machine learning and data science initiatives from problem definition through production deployment and business impact measurement. Develop predictive models, recommendation systems, forecasting, fraud detection, and customer analytics solutions using modern machine learning and foundation-model techniques. Establish experimentation and evaluation frameworks, partner with cross-functional stakeholders, present technical recommendations, mentor data scientists and AI engineers, and shape the organization’s technical direction.

Design, deliver, and continuously improve scalable production AI solutions using LLMs, RAG, agentic AI, machine learning, and document intelligence. Build cloud-native systems on Azure using software engineering, architecture, DevOps, and MLOps practices. Own AI platforms and models across deployment, monitoring, security, governance, and optimization. Lead technical initiatives, collaborate with product and business teams, mentor engineers, and translate business needs into measurable outcomes.

Lead and develop globally distributed Data and AI teams to deliver production Data/AI solutions. Drive talent development, operational excellence, stakeholder alignment, and responsible AI practices while partnering with Product and Engineering to set priorities, roadmaps, and delivery metrics.

Manages the Coordination of Benefits and Ideation & Growth portfolios, leading opportunity prioritization, forecasting, executive reporting, KPI tracking, value realization, and productivity planning. Drives modernization through AI, machine learning, automation, improved data integration, and scalable operating models. Partners with Operations, Finance, Product, Technology, Analytics, Data Science, and leadership teams to develop business cases, deploy innovation, monitor savings and revenue, and improve operational efficiency and growth outcomes.

Develop and ship production machine learning and statistical algorithms for MongoDB’s core server, query engine, and Atlas platform. The role focuses on resource scaling, release safety, monitoring, automated incident response, and query performance. Responsibilities include prototyping, testing, deployment, model feedback loops, metrics and dashboards, code reviews, and collaboration with engineering teams to deliver measurable business impact.

Lead creation of an AI-first engineering capability for database products: design reusable frameworks, ensure secure production code, guide AI-enabled delivery, set governance and guardrails, influence senior stakeholders, and mentor engineers to scale cross-product adoption.

Leads enterprise product security across Google Cloud, AWS, AI applications, and software development. Designs security solutions, develops threat-modeling frameworks, conducts code reviews and vulnerability testing, integrates secure practices into the SDLC, and creates security policies. Triages threats, assesses risks, manages corrective actions, communicates findings to technical and executive stakeholders, and validates AI-assisted security recommendations for security, resiliency, data protection, and auditability.

Lead a hands-on engineering team to design and deliver IoT and edge-to-cloud solutions that integrate AI/ML for real-time workplace insights. Architect resilient, secure pipelines, enforce data governance (FAIR), drive agentic AI adoption across the SDLC, mentor engineering talent, and split time between strategic leadership and active coding.