Top Machine Learning Jobs in Dublin

Lead strategic ownership of Mastercard's next-generation disputes platform, define product vision and roadmaps, drive AI-enabled capabilities, prioritize cross-team backlogs, partner with execs/stakeholders, and scale platform adoption and operational automation.

Lead product strategy and execution for Mastercards next-generation disputes platform. Define vision, prioritize roadmaps, partner with executives and engineering, embed AI and automation, drive cross-functional alignment, and scale platform capabilities to improve dispute resolution, customer outcomes, and operational efficiency.

Lead strategic product domains for Mastercard's next-generation disputes platform. Define vision, roadmaps, and measurable outcomes; drive AI-enabled automation and predictive decisioning; partner with execs, engineering, data science, and customers to scale platform capabilities and influence portfolio investments.

Lead strategic product domains for Mastercard's next-generation disputes platform. Define vision, prioritize roadmaps, drive AI-enabled automation, partner with engineering/data/design, engage executives and customers, and scale platform capabilities to improve dispute resolution, operational efficiency, and customer outcomes.

Lead product strategy and execution for Mastercard's next-generation disputes platform. Define vision, prioritize roadmaps, drive AI-enabled automation and analytics, partner with engineering, design, and stakeholders, and scale platform capabilities globally to improve customer outcomes and operational efficiency.

Lead strategic product domains for Mastercard's next-generation disputes platform, define roadmaps, prioritize investments, and scale AI-enabled capabilities across engineering, data science, and design teams to improve dispute resolution, automation, and customer outcomes.

Lead product strategy and execution for Mastercard's next-generation disputes platform. Define domain vision, prioritize multi-team roadmaps, drive AI-enabled capabilities, partner with engineering, data science, and stakeholders, and influence executive investment decisions to scale platform modernization and improve dispute resolution outcomes.

Lead strategy and execution for Mastercard's next-generation disputes platform. Define domain vision, prioritize roadmaps, own large-scale product backlogs, and drive AI-enabled automation and predictive decisioning. Partner with engineering, data science, design, and executives to deliver scalable platform capabilities, influence investments, and scale global product initiatives while coaching product teams and ensuring customer-centric outcomes.

Lead product strategy and execution for Mastercard's next-generation disputes platform. Define domain vision, prioritize roadmaps, drive AI-enabled automation and predictive decisioning, partner with engineering, data science, and stakeholders, and influence executive investment to scale platform capabilities and improve customer and operational outcomes.

Lead strategy and execution for Mastercard's next‑generation disputes platform. Own product vision, roadmaps, and large-scale backlogs; drive AI/automation adoption; partner with engineering, data science, design, and stakeholders; influence executive investment decisions; and scale platform capabilities that improve customer outcomes, operational efficiency, and platform adoption.

Lead product strategy and execution for Mastercard's next-generation disputes platform. Define platform domains, prioritize roadmaps, embed AI/automation, partner with engineering and stakeholders, and drive global product modernization and measurable business outcomes.

Conduct original research applying machine learning, deep learning, and NLP to extract patterns from large and unstructured datasets; implement and back-test algorithms in high-quality code; document findings and collaborate with trading teams to deploy research-driven models.

Develop and operate large-scale identity protection and anti-fraud systems defending Microsoft infrastructure against signup, telecom, phishing, spam, and revenue-share attacks. Responsibilities include designing, coding, testing, debugging, deploying, and supporting resilient features; applying machine learning and threat intelligence; analyzing metrics; ensuring reliability; collaborating cross-functionally; and participating in on-call rotation.

Leads CEL’s enterprise AI adoption by developing the AI roadmap, identifying and scaling use cases, integrating AI with ERP, CAD/PLM, CRM, Microsoft 365, and other systems, and establishing responsible AI governance. The role partners with business, IT, vendors, and external providers; develops adoption metrics; trains employees; manages change; and supports AI-enabled engineering, predictive maintenance, analytics, and intelligent infrastructure initiatives.

Design and implement scalable cloud, data, and AI architectures for an airline customer. Translate aviation business requirements into technical solutions, lead architecture reviews, advise engineering teams, and provide implementation guidance. Act as the customer’s technical advisor and escalation point while collaborating with internal product and engineering teams. Drive technology best practices, optimization, security, performance, and successful solution adoption.

Perform malware and threat research across the attack lifecycle, validate and improve Falcon detections, collaborate with engineering and ML teams, automate analysis, support external security testing, and translate findings into product protections.

Support strategic AI adoption analysis for financial-services clients by conducting interviews and workshops, analyzing documentation, mapping business processes, identifying AI opportunities, and assessing initiative impact, effort, and risk. Contribute to AI Pathfinder reports, presentations, business cases, and project roadmaps while communicating technical findings to non-technical stakeholders.

Lead product vision, strategy, and roadmap for Claim Review products. Collaborate with engineering, AI/ML, analytics, and GTM teams to build data-driven, cloud-based solutions. Prioritize features, measure KPIs, ensure successful launches, and scale client-proven innovations while monitoring market and regulatory trends.

Lead product strategy and execution for transaction data, consent, authentication, and AI-enabled data services. Define roadmaps, drive API-driven platform delivery, validate customer needs, collaborate with engineering, privacy, security, and legal, and use data and AI tools to measure and improve product outcomes.

Leads clinical data science delivery and team development, designing advanced statistical models and machine learning methods for clinical research. Oversees data analysis, management, regulatory compliance, and trial optimization while collaborating with clinical, biostatistical, and regulatory teams. Communicates complex insights to senior stakeholders and external partners and drives innovation across clinical development programs.

Graduate engineering opportunities across Analog Devices’ Ireland locations in electronics, semiconductor, software, AI, robotics, manufacturing, research, quality, and supply chain. Graduates may work in IC design, embedded software, verification, RF design, process engineering, testing, packaging, reliability, and related functions. The program includes rotations, learning opportunities, relocation assistance, and access to advanced facilities. Recruitment begins in September 2026 on a rolling basis. No travel is required.

Graduate software engineering opportunities involving embedded software, software systems, software development, AI, machine learning, UI/UX design, and cloud architecture. Graduates collaborate with hardware teams on planning, system architecture, development, troubleshooting, debugging, and testing across applications including IoT, automotive radar, healthcare monitoring, and 5G. The role includes a graduate rotation program, learning opportunities, and exposure to advanced semiconductor technologies.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Lead a multidisciplinary engineering team building scalable Quantum and AI/ML-enabled payment products. Define requirements, drive agile delivery, research/design solutions, manage projects, coach talent, and engage with external partners and events.

Lead a multidisciplinary engineering team to design, build and deliver scalable AI and quantum-enabled payment products. Define requirements, drive project execution using agile and AI-assisted processes, mentor engineers, coordinate with data scientists, and represent the team internally and externally.