Senior AI & Machine Learning Engineer

My client is looking for a Senior AI & Machine Learning Engineer with a minimum of 5 years of experience to join their organisation in Limerick. This is a permanent role.

Key Skills and Experience

• 5+ years' experience in Machine Learning Engineering, Applied Data Science, AI Engineering, or a similar hands-on technical role delivering production-grade AI and machine learning solutions.

• Strong expertise applying and deploying machine learning models within manufacturing, industrial, IoT, and operational technology environments, including MES, SCADA, and sensor-driven platforms.

• Proven experience working with TensorFlow, PyTorch, and Scikit-learn, alongside practical expertise deploying, managing, and scaling models across AWS, Azure, and GCP cloud environments.

• Hands-on experience designing and delivering Generative AI solutions, including RAG architectures, embedding optimisation, vector databases, evaluation frameworks, prompt engineering, and agentic workflows.

• Strong understanding of MLOps practices, including CI/CD pipelines, Docker, Kubernetes, model monitoring, automated retraining strategies, model lineage, governance controls, and operational support.

Responsibilities

• Design, develop, and deploy machine learning solutions supporting predictive maintenance, anomaly detection, defect classification, computer vision inspection, and operational optimisation initiatives.

• Build and maintain scalable AI and machine learning pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, monitoring, governance, and continuous improvement activities.

• Develop Generative AI and retrieval-based solutions using structured and unstructured industrial datasets, including technical documentation, operational procedures, maintenance records, and equipment data.

• Implement robust evaluation, monitoring, and governance frameworks to ensure model accuracy, explainability, traceability, compliance, and alignment with operational KPIs.

• Work closely with engineering, manufacturing, operations, and technology teams to identify innovation opportunities and deliver practical AI-driven business outcomes.

• Support the adoption of modern AI, machine learning, and analytics capabilities by contributing to technical strategy, best practices, architectural standards, and continuous improvement initiatives across the organisation.