Model Development & Deployment

• Architect, train, and operationalize machine learning models for predictive maintenance, anomaly detection, and manufacturing process optimization.
• Build Generative AI applications such as automated reporting systems, intelligent virtual assistants, and production scenario simulation tools.
• Convert experimental AI/ML algorithms into scalable, production-grade solutions by applying MLOps best practices.

Data Engineering & Integration

• Design and maintain reliable data pipelines to ingest, cleanse, and transform sensor, MES, and IoT data for model training and real-time inference.
• Integrate AI solutions with factory automation systems and Manufacturing Execution Systems (MES) to enable data-driven operational decisions.

Predictive Analytics & Quality Control

• Leverage machine learning and AI techniques to predict equipment breakdowns, optimize manufacturing schedules, and enhance product quality.
• Implement computer vision and deep learning solutions for automated defect identification and quality inspection processes.

Automation & Continuous Improvement

• Develop AI-powered automation workflows and GenAI conversational solutions to minimize manual processes and improve operational productivity.
• Track model performance, identify model drift, and streamline automated retraining workflows to ensure sustained model reliability and accuracy.

Collaboration & Reporting

• Partner with engineering, operations, and IT teams to align AI and GenAI initiatives with broader manufacturing goals.
• Present actionable insights, recommendations, and performance results through dashboards and AI-generated narrative reports.

Required Skills

• At least 7 years of relevant working experience.
• Demonstrated proficiency in programming languages such as Python, R, or Java.
  
• Practical experience working with machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
• Strong knowledge of machine learning methodologies, deep learning models, and statistical analysis techniques.
• Familiarity with MLOps technologies and platforms such as MLflow, KServe, Docker, and Kubernetes.
• Experience implementing CI/CD workflows and deployment automation practices.

Domain Knowledge

• Solid understanding of manufacturing operations, MES platforms, and industrial automation systems.
• Hands-on experience applying predictive maintenance, anomaly detection, and real-time analytics in manufacturing environments.

Data Engineering & Data Handling

• Expertise in data cleansing, feature engineering, and managing high-volume sensor and IoT datasets.
• 
  Working knowledge of SQL, NoSQL databases, and cloud-based infrastructure for data storage and model deployment.
  

Soft Skills

• Excellent analytical and critical-thinking abilities with a strong problem-solving mindset.
• Strong written and verbal communication skills with the ability to explain technical concepts clearly.
• Proven ability to collaborate effectively across cross-functional teams while managing competing priorities in dynamic environments.

To apply, please visit www.gmprecruit.com and search for Job Reference:

We regret that only shortlisted candidates will be notified.

GMP Technologies (S) Pte Ltd | EA License: 11C3793 | EA Personnel: Bautista Gia Grace De Guzman | Registration No: R23111973