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Machine Learning/GenAI Engineer

3 weeks ago

Woodlands North Region, Singapore UST Full time

Machine Learning/GenAI Engineer -
Smart Manufacturing & AI Solutions

Core Responsibilities:

  • To design, develop, and deploy advanced AI/ML and Generative AI (GenAI) solutions that optimize manufacturing operations in a high-volume drive production environment.
  • This role focuses on leveraging machine learning, predictive analytics, and automation to improve yield, reduce downtime, and enable smart factory capabilities aligned with Industry 4.0 principles.
  • Model Development & Deployment
  • Build and implement machine learning models for predictive maintenance, anomaly detection, and process optimization.
  • Develop GenAI-powered applications for automated reporting, intelligent chatbots, and simulation of manufacturing scenarios.
  • Translate research-level algorithms into production-ready solutions using MLOps best practices.
  • Data Engineering & Integration
  • Develop robust data pipelines to collect, clean, and transform sensor, MES, and IoT data for model training and inference.
  • Integrate AI models with factory control systems and MES for real-time decision-making.
  • Predictive Analytics & Quality Control
  • Apply AI techniques to forecast equipment failures, optimize production schedules, and enhance product quality.
  • Use computer vision and deep learning for automated defect detection and quality assurance.
  • Automation & Continuous Improvement
  • Implement AI-driven workflows and GenAI-based conversational assistants to reduce manual interventions and accelerate cycle times.
  • Monitor model performance, detect drift, and automate retraining processes.
  • Collaboration & Reporting
  • Work closely with engineers and IT teams to align AI and GenAI solutions with factory goals.
  • Communicate insights and recommendations to stakeholders through dashboards and
    natural language summaries generated by GenAI
    .

Required Skills:

  • Technical Expertise
  • Proficiency in Python, R, or Java; experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Strong knowledge of machine learning algorithms, deep learning architectures, and statistical methods.
  • Familiarity with MLOps tools (MLflow, KServe, Docker, Kubernetes) and CI/CD pipelines.
  • Domain Knowledge
  • Understanding of manufacturing processes, MES systems, and industrial automation technologies.
  • Experience with predictive maintenance, anomaly detection, and real-time analytics.
  • Data Handling
  • Expertise in data preprocessing, feature engineering, and working with large-scale sensor/IoT datasets.
  • Knowledge of SQL/NoSQL databases and cloud platforms for data storage and model deployment.
  • Soft Skills
  • Strong problem-solving ability, analytical mindset, and effective communication skills.
  • Ability to work in cross-functional teams and manage multiple priorities in a fast-paced environment.