Top Machine Learning Jobs in Dublin

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Lead Dotmatics’ AI governance program by developing frameworks, risk tiering, use-case registries, policies, controls, and reporting aligned with regulations and standards. Coordinate the AI Governance Council and Siemens consortium, assess AI risks across product and business functions, embed controls into the SDLC, respond to customer due diligence, and deliver training. The role requires executive communication, cross-functional influence, technical understanding of AI/ML systems, and extensive information security, technology risk, compliance, and regulated-industry experience.

Build and optimize machine learning models and data pipelines for Workday’s de-identification and anonymization engine. Apply privacy techniques including differential privacy, k-anonymity, l-diversity, and t-closeness; fine-tune NER and pattern-matching models; and operate high-throughput Spark, EMR, and SageMaker pipelines in production. Collaborate with platform, infrastructure, product, legal, and compliance teams to develop scalable ML systems, data governance frameworks, and clear technical recommendations addressing privacy-utility trade-offs.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Leads commercial performance for global and regional eCommerce markets, improving revenue, margin, EBIT, conversion, AOV, demand shaping, customer experience, and retention. Partners with market leaders to diagnose performance, recommend actions, align improvement plans, govern KPI frameworks, and ensure adoption. Leads data storytellers, establishes analytical and measurement standards, develops global playbooks, and influences senior stakeholders across a global matrix organization.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

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.

Develop, validate, deploy, and maintain machine learning solutions for medical device manufacturing and CAD/CAM systems. Build deep learning and multimodal AI models using computer vision, 3D geometry, meshes, images, and structured data. Integrate models into production systems, conduct performance analysis, maintain ML workflows, and translate research into practical manufacturing applications while collaborating with engineering, manufacturing, and product teams.

Develop and maintain high-load, real-time personalization services for global e-commerce platforms. Improve shopper experiences and business KPIs through applied machine learning, user interaction modeling, personalization and recommender systems, hypothesis validation, and A/B testing. Collaborate with engineering teams and business stakeholders to research, deliver, and communicate personalization capabilities and outcomes.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own the full enterprise customer journey from kickoff through adoption and ongoing value realization. Build executive and technical stakeholder relationships, lead QBRs and EBRs, translate product performance into business outcomes, manage risks and escalations, provide strategic ecommerce recommendations, maintain success plans, and partner with Account Management on retention and expansion.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

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.

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 and manage an agile software engineering team building scalable AI and Quantum-infused payment solutions; define requirements, drive delivery, mentor talent, collaborate with data scientists and UI/UX, and represent the team externally.

Lead a multidisciplinary engineering team to design, build and scale AI and Quantum-enabled payment solutions. Drive agile delivery, define requirements, productionize Python/Jupyter solutions, deploy on Kubernetes, mentor talent, and engage with internal and external innovation partners.

Lead and manage a multidisciplinary engineering team building scalable products that combine Quantum and AI/ML technologies. Drive project delivery using agile and AI-assisted processes, define requirements, design scalable solutions, engage external partners, and mentor engineering leaders to bring innovations to market globally.

Lead and manage a multidisciplinary engineering team to design, build and deliver scalable software products that combine Quantum and AI/ML technologies; define requirements, drive agile execution, mentor talent, and engage with internal and external partners to bring innovative payment solutions to market.

Lead and manage an agile software engineering team to design, build and scale innovative products that combine Quantum and AI/ML. Define requirements, drive project execution, collaborate with data scientists and engineers, and deploy solutions using Python, Jupyter and containerized virtual environments (including Kubernetes). Coach and grow talent, ensure compliance with standards, and represent the team externally.

Lead and manage a software engineering team in Mastercard Foundry R&D focused on Quantum, AI/ML. Define requirements, design scalable solutions, drive agile project delivery, collaborate with data scientists and engineers, deploy Python/Jupyter-based systems to production (including Kubernetes), and coach talent while promoting innovation.

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.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.