Machine Learning Engineer (Manufacturing)
Key Responsibilities
Design, build, and deploy machine learning models for manufacturing use cases
Develop and maintain end‑to‑end ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment
Prepare and curate training datasets with domain subject‑matter experts
Collaborate with cross‑functional teams including:
Manufacturing engineers
Process engineers
IT / OT teams
Data scientists and analysts
Integrate ML solutions with production systems (e.g., MES, SCADA, IoT platforms)
Own feature engineering and data pipeline reliability
Monitor model performance in production and implement retraining and continuous improvement processes
Work with structured and unstructured industrial datasets (sensor data, time series, images)
Ensure solutions are scalable, reliable, and aligned with best practices in MLOli>
Document models, pipelines, and processes to support maintainability and knowledge transfer
Desired Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering (Mechanical, Industrial, Electrical, or related) or equivalent practical experience. ~5 years of experience in machine learning engineering or applied data science, with proven experience in a manufacturing, industrial, or IoT environment. Strong technical skills in
Machine Learning & Data Science, programming, MLOps, data engineering, and AI tools.
Technical Skills
Machine Learning & Data Science
Supervised and unsupervised learning techniques
Time‑series analysis and anomaly detection
Computer vision applications (preferred)
Model evaluation, validation, and tuning
Programming & Tools
Proficiency in Python
ML libraries: TensorFlow, PyTorch, Scikit‑learn
Strong SQL skills and experience with large datasets
MLOps & Engineering
Deploying models securely into production environments
Docker, Kubernetes, CI/CD pipelines
Model monitoring and versioning
Data Engineering
Data pipelines and ETL processes
Exposure to cloud platforms (AWS, Azure, or GCP)
AI Tools
Proficient with AI Tools and Assistants (e.g., Claude, ChatGPT, GitHub Copilot) for development and research
Key Competencies
Strong problem‑solving skills with a practical, results‑driven mindset
Ability to translate business and operational problems into ML solutions
Effective stakeholder communication, including non‑technical audiences
Collaborative team player with cross‑functional experience
High attention to detail and data quality
Ability to break down work into deliverables
Company
Digital Manufacturing Ireland
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