AI / ML Engineer (Smart Manufacturing & GenAI Solutions)

AI / ML & GenAI Solution Development

• Design, develop, and deploy AI/ML and Generative AI solutions to optimize high-volume drive manufacturing operations.

• Build machine learning models for predictive maintenance, anomaly detection, yield improvement, and process optimization.

• Develop GenAI-powered applications such as automated reporting tools, intelligent chatbots, and manufacturing scenario simulations.

• Convert research-based algorithms into scalable, production-ready solutions following MLOps best practices.

Data Engineering & System Integration

• Develop and maintain data pipelines for sensor, MES, and IoT data ingestion, transformation, and model inference.

• Integrate AI models with MES and factory control systems to enable real-time decision-making.

• Ensure seamless deployment within CI/CD and containerized environments.

Predictive Analytics & Quality Engineering

• Implement AI-driven predictive analytics to forecast equipment failures and optimize production scheduling.

• Apply computer vision and deep learning techniques for automated defect detection and quality assurance.

• Enhance product quality and reduce downtime using data-driven insights.

Automation & Continuous Optimization

• Deploy AI-driven workflows and GenAI conversational assistants to reduce manual intervention.

• Monitor model performance, detect model drift, and automate retraining pipelines.

• Continuously improve AI systems aligned with Industry 4.0 smart factory initiatives.

• Collaborate with manufacturing engineers, automation teams, and IT stakeholders.

• Present AI-driven insights through dashboards and GenAI-generated summaries.

• Align AI solutions with overall factory performance goals.

Requirements:

• 5-10 years of relevant working experience.
• Proficiency in programming languages such as Python, R, or Java, with hands-on experience using machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.

• Strong understanding of machine learning algorithms, deep learning architectures, and statistical analysis techniques.

• Experience with MLOps tools and platforms such as MLflow, KServe, Docker, and Kubernetes, along with familiarity in implementing CI/CD pipelines.

• Solid understanding of manufacturing processes, Manufacturing Execution Systems (MES), and industrial automation technologies.

• Practical experience in areas such as predictive maintenance, anomaly detection, and real-time data analytics.

• Expertise in data preprocessing, feature engineering, and handling large-scale sensor or IoT datasets.

• Familiarity with SQL and NoSQL databases, as well as cloud platforms used for data storage and machine learning model deployment.

To apply, please visit and search for Job Reference: 3WR7VW8V

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

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