AI/ML Engineer

AI/ML Engineer – Consultant Level 📍 The Dock, Dublin Want to turn the latest advances in AI into products and services that solve real-world problems? We’re looking for an experienced AI/ML Engineer to join The Dock, Accenture’s flagship R&D and Global Innovation Centre in Dublin. The Dock brings together strategists, designers, engineers, data scientists and entrepreneurs to explore emerging technologies and build the next generation of AI, generative AI and agentic solutions. As part of this multidisciplinary community, you’ll take AI ideas from exploration and rapid prototyping through to robust, scalable solutions. You’ll work across the model lifecycle, applying advances in machine learning, deep learning, large language models and natural language processing to complex business and industry challenges. What you’ll be doing: - Design, develop and evaluate AI and machine-learning solutions for R&D, product and commercial applications. - Guide key stages of the model lifecycle, including data acquisition, preprocessing, feature engineering, training, optimisation and benchmarking. - Build solutions using large language models, natural language processing, prompt engineering and context engineering. - Evaluate emerging models, open-source frameworks, APIs and cloud services to identify the right approach for each problem. - Rapidly prototype AI solutions to test feasibility, validate assumptions and accelerate learning. - Collaborate with scale and engineering teams on deployment, production monitoring and model lifecycle management. - Work with designers, product managers, engineers and business stakeholders to translate complex requirements into robust, scalable and efficient AI solutions. - Build retrieval-grounded solutions using structured and unstructured data, including vector databases and knowledge graphs. - Develop and integrate secure APIs that make AI capabilities accessible to wider products and platforms. - Apply strong software-engineering practices across version control, testing, code reviews, CI/CD and MLOps. - Mentor junior engineers, contribute to technical decisions and help raise engineering standards across the team. - Champion Responsible AI, data privacy, security and appropriate governance throughout the development lifecycle. What we’re looking for: You’ll bring: - Substantial professional experience designing and implementing analytics, machine-learning or AI systems for research, product or commercial use. Approximately five years of relevant experience is desirable, but demonstrated capability and delivery impact matter more than a specific number of years. - Deep hands-on knowledge of machine learning, deep learning, data science and data-modelling techniques. - Strong practical experience with large language models and natural language processing. - Advanced programming proficiency in Python. - Experience applying prompt and context engineering to real-world AI solutions. - The ability to benchmark and evaluate emerging AI models, tools and open-source frameworks. - Experience with cloud-native AI platforms such as Azure Machine Learning, AWS SageMaker or Google Vertex AI. - An understanding of how models are deployed, monitored and managed in production, ideally with hands-on experience operationalising AI at scale. - Experience working in collaborative, multidisciplinary and agile teams with distributed stakeholders. - Strong communication skills, including the ability to explain complex AI concepts and technical trade-offs to non-technical audiences. - Experience mentoring, coaching or supporting the development of junior team members. - A relevant bachelor’s degree or higher in Computer Science, Data Science, Mathematics, Artificial Intelligence or a related discipline. Even better if you have experience with: - Retrieval-Augmented Generation (RAG) - Vector databases and knowledge graphs - Relational and document databases - SQLAlchemy - Databricks - Apache Beam and cloud-native data pipelines - Apache Spark or Hadoop - Docker and Kubernetes - MLOps platforms such as MLflow or Kubeflow - Secure RESTful APIs using frameworks such as FastAPI - CI/CD, automated testing and production observability - Git, branching strategies, pull requests and code reviews - GitHub Copilot or other AI-assisted development tools - Data-security and data-privacy principles - Working within a large, matrixed organisation Why this role? The Dock operates across the full innovation spectrum, from exploring new AI capabilities to building solutions that can create measurable value in the real world. This is an opportunity to work in an environment where experimentation is encouraged, but practical outcomes matter. You’ll collaborate with experts from across technology, design, product and business strategy, giving you the opportunity to approach complex challenges from multiple perspectives. You’ll also stay close to the latest developments in AI research while gaining experience turning those advances into secure, responsible and scalable products and services. If you’re an experienced AI/ML Engineer who enjoys navigating ambiguity, testing emerging technologies and turning promising ideas into working solutions, we’d love to hear from you. #MachineLearning #AIEngineering #GenerativeAI #LLM #NLP #Python #MLOps #ResponsibleAI #ArtificialIntelligence #DublinJobs