Senior Machine Learning / AI Engineer

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