Senior AI & Machine Learning Engineer

apartmentMorgan McKinley placeLimerick calendar_month 

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.
  • Demonstrated ability to collaborate with operational stakeholders, engineering teams, and subject matter experts to translate complex business challenges into scalable AI, machine learning, and analytics solutions.
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.
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