AI Engineer

• Identify high-value AI use cases by partnering with business functions to understand operating priorities and pain points.
• Develop and maintain a prioritized Applied AI roadmap that aligns with Continuous Improvement objectives, business strategy, and enterprise priorities.
• Lead the design, development, and deployment of AI-powered product features and internal solutions.
• Partner with functional leads and their teams align priorities, dependencies, and delivery timelines.
• Establish and promote best practices for experimentation, model evaluation, and lifecycle management.

Applied AI Lead

Machine Learning Engineer

• Evolve the Interactive Learning Plugin's recommendation system
• Build and operate applied models for recommendation system
• Define what recommendation quality means and develop measures
• Ship incremental improvements and integrate them into the existing recommender
• Partner with software engineers and data analysts to productionize models

Senior Machine Learning Engineer, Developer Advocacy

• Lead and mentor a team of Applied Scientists and AI/ML Engineers, fostering a culture of technical excellence and scientific rigor
• Lead the technical strategy for AI/ML-based solutions focused on extracting actionable value and insights from both structured CRM data and unstructured content
• Build the intelligence within our AI-native CRM, including the design of autonomous agentic workflows and real-time reasoning engines that execute business actions safely at scale
• Partner closely with the AI Platform team to drive the overarching strategy for large language model operations (LLMOps), ensuring infrastructure supports efficient experimentation and robust deployment
• Apply deep scientific intuition to the design of AI systems, ensuring that models and data-intensive solutions are optimized for customer centricity and real-world performance
• Act as a technical authority and multiplier across the AI/ML and data ecosystem, shaping the AI engineering roadmap and setting the bar for how we leverage the modern AI stack
• Lead as a high-impact individual contributor on our most critical systems, balancing a deep love for building with the ability to delegate effectively and grow the team’s technical capabilities

Principal AI/ML Scientist – Engineer

• Build core ML systems for a proactive AI product.
• Own end-to-end processes: data prep, training, evaluation.
• Collaborate with research and engineering teams.
• Mentor other ML engineers.
• Iterate quickly on system designs and improvements.

Senior Machine Learning Engineer

• Build and improve ML components across data, training, evaluation, and inference.
• Fine-tune and adapt models as part of larger production systems.
• Implement evaluation and testing to understand model behavior.
• Help build and maintain data pipelines for real-world and synthetic data.
• Debug model issues, performance problems, and production incidents.
• Ship improvements iteratively and learn from real user feedback.
• Work closely with senior ML engineers and product teams.
• Work under real production constraints: latency, cost, reliability, and safety

Member of Technical Staff, Machine Learning

• Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets.
• Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle.
• Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding.
• Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
• Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
• Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

Staff AI Engineer

• Build customer-facing and internal product features end to end.
• Develop web flows, backend APIs, admin tools, dashboards and operational systems.
• Support products across insurance, payments, savings, investing, travel and financial services.
• Work with product, design, mobile and operations teams to launch fast.
• Integrate APIs, handle data flows and improve production reliability.
• Use analytics, feedback and production issues to improve features after launch.
• Help build tools that reduce manual work and improve speed across the business.

Full Stack Software Engineer – AI Neobank App

• Build AI agents, workflows, tools and automations that solve real customer, product and operations problems.
• Apply LLMs, retrieval, tool calling, evaluations, guardrails and automation to practical financial workflows.
• Create AI-assisted experiences for onboarding, support, KYC, risk review, CRM, operations, document handling and product intelligence.
• Work with product and engineering teams to identify what is worth building, then build it quickly and improve it in production.
• Design around real constraints: accuracy, hallucination risk, latency, cost, security, compliance and user trust.
• Turn manual processes into reliable AI-enabled systems that can scale.

Applied AI Engineer

• Build AI-powered workflows, assistants, agents and automation systems.
• Apply AI across customer support, CRM, onboarding, claims, renewals, payments, operations and internal tools.
• Work with product and engineering teams to turn manual processes into scalable AI-native systems.
• Build integrations with LLMs, internal data, APIs, documents, knowledge bases and business systems.
• Design evaluation, monitoring and fallback flows so AI outputs are useful, safe and reliable.
• Prototype quickly, test with users or operators, then productionize what works.
• Improve speed, quality and consistency across workflows using AI where it creates real business value.

Applied AI Engineer – AI Neobank App

• Build and ship Android features using Kotlin.
• Create clean mobile flows for insurance, payments, claims, renewals and financial services.
• Work with product and design to simplify complex user journeys.
• Integrate backend APIs and ensure mobile flows are stable, secure and reliable.
• Improve app performance, crash rate, loading states, responsiveness and memory usage.
• Use analytics, user behaviour and production issues to improve the product.
• Build AI-assisted mobile experiences only where they genuinely improve the user journey.

Mobile Developer – AI Neobank App

LLM Engineer

• You will own, build, and run your startup in fields such as AI Infrastructure.
• You will embark on an extensive personal development journey crafted by unicorn founders.
• You will receive support in hiring through our network to over 50,000 professionals and advice as well as best practices from serial entrepreneurs.
• You will iterate your product with us until having reached product-market-fit and receive support in building up a sales force or creating a marketing engine respectively.

AI Infrastructure Co-Founder, CSO

• Work with business and technology stakeholders to identify, shape and prioritise AI use cases with clear business value
• Design, build and iterate AI proof of concept solutions using modern AI, machine learning, generative AI, automation and data engineering techniques
• Assist the Governance team assess the feasibility, value, risks and limitations of AI PoCs
• Develop AI prototypes that demonstrate practical value
• Translate PoC learnings into clear recommendations for the Governance team
• Design solutions with production-readiness in mind
• Build AI-enabled services, APIs, workflows, prompts, retrieval pipelines
• Apply responsible AI practices
• Collaborate with architects and engineering teams to align PoC designs with CR2’s target architecture
• Work with Product Management, Business Analysts and Subject Matter Experts
• Document technical designs, assumptions, dependencies, evaluation results, risks and productionisation recommendations
• Monitor developments in AI tools, frameworks, models and cloud services
• Support knowledge sharing and enablement across teams

• Develop documentation processes and guidelines for AI policy
• Work on AI initiatives involving chatbots and document control
• Design and maintain AI chatbot functionalities
• Collaborate with stakeholders for requirement finalization
• Automate internal operational pipelines

• Research, design, develop, fine-tune, and evaluate LLMs, intelligent agents, and deep learning models for AI security and system optimisation.
• Create advanced tools for automated red-teaming, vulnerability detection, adversarial attack simulation, and intelligent defences.
• Implement and deploy AI/LLM-powered features as robust, scalable, and secure components within the client's security platforms.
• Optimise AI/LLM models for inference speed, cost-efficiency, and resource utilisation in production.
• Develop and maintain pipelines for end-to-end AI/LLM workflows covering data preprocessing, training, fine-tuning, validation, deployment, and monitoring.
• Proactively monitor model performance and behaviour in production, addressing safety, alignment, and security vulnerabilities.
• Apply software engineering best practices to AI/LLM workflows for secure and seamless deployments.
• Partner with cross-functional teams, including researchers and engineers, to productionise cutting-edge AI/LLM techniques and integrate them into the client's products.
• Translate technical advancements into practical solutions aligned with customer needs and business objectives.
• Communicate findings and solutions through documentation and presentations for data-driven decision-making.
• Develop tools and strategies to detect and mitigate vulnerabilities such as prompt injection and data poisoning threats.
• Investigate and utilise advancements in Reinforcement Learning from Human Feedback (RLHF) to improve AI model reliability and alignment.
• Continuously stay updated on industry trends and research to integrate state-of-the-art AI/LLM advancements into the platform.

AI/ML Engineer

• Build and ship end-to-end AI applications (backend, data, APIs, UI)
• Turn ambiguous problems into working software quickly
• Use AI-native tools to accelerate delivery
• Apply key AI patterns (RAG, agents, prompt engineering, evaluation)
• Build and scale the AI Platform on Azure (multi-region)
• Own core components: APIM, identity, networking, observability, data
• Establish CI/CD, IaC, testing, and deployment standards
• Integrate with internal and third-party systems (CRM, CX platforms)
• Work with tools like Zendesk, Genesys, Intercom, Microsoft 365
• Build APIs, webhooks, and event-driven systems
• Embed GDPR, ISO 27001, SOC 2 (and others) into the platform
• Partner with Security/GRC on data protection and access control
• Partner with Product on roadmap and build-vs-buy decisions
• Document systems, architecture, and processes
• Monitor production systems and improve performance, cost, and reliability

Machine Learning Engineer jobs in Ireland

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Applied AI Lead

Senior Machine Learning Engineer, Developer Advocacy

Principal AI/ML Scientist – Engineer

Senior Machine Learning Engineer

Member of Technical Staff, Machine Learning

Staff AI Engineer

Full Stack Software Engineer – AI Neobank App

Applied AI Engineer

Applied AI Engineer – AI Neobank App

Mobile Developer – AI Neobank App

AI Infrastructure Co-Founder, CSO

AI Engineer

AI Engineer

AI/ML Engineer

Full Stack AI Engineer