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YokogawaPosted 1 month ago

Industrial Automation AI Engineer

On-siteBedok New Town, Singapore

Full TimeBachelors DegreeEnterprise

Job Summary

Develop Generative AI applications using LLMs, RAG, embeddings, or vector databases to support predictive analytics, time-series analysis, and anomaly detection in asset-intensive industries. Deploy AI solutions across cloud, on-premises, and edge environments while leveraging frameworks like TensorFlow, PyTorch, and Scikit-learn. Integrate hands-on experience with sensor data, maintenance records, and technical documents alongside familiarity with SCADA, DCS, PLC, and Industrial IoT platforms. Apply MLOps practices and explore agentic AI, multi-agent systems, and reinforcement learning to drive reliability analytics and condition-based maintenance strategies.

Required Qualifications

  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering or a related discipline
  • At least 3 years of hands-on experience in AI, machine learning, data science or advanced analytics
  • Strong programming experience in Python and common data science or machine learning libraries
  • Experience with frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn or equivalent
  • Experience in predictive analytics, time-series analysis, forecasting, anomaly detection or optimisation
  • Hands-on experience developing Generative AI applications using LLMs, RAG, embeddings or vector databases
  • Experience deploying AI solutions in cloud, on-premises or edge environments
  • Experience in oil and gas, utilities, mining, manufacturing, energy or other asset-intensive industries
  • Knowledge of predictive maintenance, condition-based maintenance or reliability analytics
  • Familiarity with SCADA, DCS, PLC, historians, smart sensors or Industrial IoT platforms
  • Exposure to MLOps, agentic AI, multi-agent systems, deep learning or reinforcement learning
  • Experience working with sensor data, time-series data, maintenance records or technical documents

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