OverviewJob Title: Machine Learning Engineer (Manufacturing)ResponsibilitiesDesign, build, and deploy machine learning models for manufacturing use casesDevelop and maintain end-to-end ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deploymentPrepare and curate training datasets with domain SMEsCollaborate with cross-functional teams including: Manufacturing engineers, Process engineers, IT / OT teams, Data scientists and analystsIntegrate ML solutions with production systems (e.g., MES, SCADA, IoT platforms)Own feature engineering and data pipeline reliabilityMonitor model performance in production and implement retraining and continuous improvement processesWork with structured and unstructured industrial datasets (sensor data, time series, images)Ensure solutions are scalable, reliable, and aligned with best practices in MLOpsDocument models, pipelines, and processes to support maintainability and knowledge transferDesired QualificationsBachelor’s or Master’s degree in Computer Science, Data Science, Engineering (Mechanical, Industrial, Electrical, or related) or equivalent practical experienceApproximately 5 years of experience in machine learning engineering or applied data scienceProven experience in a manufacturing, industrial, or IoT environmentTechnical SkillsMachine Learning & Data Science: Strong understanding of supervised and unsupervised learning techniques; Experience with time-series analysis and anomaly detection; Familiarity with computer vision applications (preferred); Model evaluation, validation, and tuningProgramming & Tools: Proficiency in Python; Experience with ML libraries such as TensorFlow / PyTorch, Scikit-learn; Strong SQL skills and experience with large datasetsMLOps & Engineering: Experience deploying models securely into production environments; Familiarity with Docker / Kubernetes; CI/CD pipelines; Model monitoring and versioningData Engineering: Experience with data pipelines and ETL processes; Exposure to cloud platforms (AWS, Azure, or GCP)AI Tools: Proficient with AI Tools and Assistants for development and researchKey CompetenciesStrong problem-solving skills with a practical, results-driven mindsetAbility to translate business and operational problems into ML solutionsEffective stakeholder communication, including non-technical audiencesCollaborative team player with cross-functional experienceHigh attention to detail and data qualityAbility to breakdown work into deliverablesCompanyDigital Manufacturing IrelandQualificationsEducational level: Senior (5+ years of experience)Language requirementsNot specifiedSpecific requirementsNot specified
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