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.

Domain Knowledge

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.

Data Management

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.

Soft Skills

Strong analytical thinking and problem-solving capabilities, supported by effective communication skills.
Ability to collaborate within cross-functional teams and manage multiple tasks in a dynamic, fast-paced environment.

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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AI / ML Engineer (Smart Manufacturing & GenAI Solutions)