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Yokogawa

Industrial automation and process control solutions

Artificial Intelligence/Machine Learning Engineer

Applied Machine LearningUpdated on Nov 15
Full-timeMuharraq, BahrainNo salary listedIn-person

About the Job

Requirements

  • Bachelor's or master's degree in Chemical Engineering, Artificial Intelligence, Machine Learning, or a related field.
  • At least 6 years of hands-on experience executing AI/ML and process simulation projects.
  • Proven project delivery experience in industrial or energy sectors; oil and gas experience is preferred.
  • Knowledge of upstream, midstream, and downstream oil and gas processes, instrumentation, and control systems.
  • Expertise developing dynamic process simulations using PFDs and P&IDs and troubleshooting.
  • Proficiency handling large-scale, time-series, and sensor/IoT data in industrial contexts.
  • Familiarity with real-time data challenges and solutions in high-stakes industrial environments.
  • Strong foundation in supervised, unsupervised, and reinforcement learning algorithms, statistical modeling, and optimization techniques.
  • Strong experience with classical machine learning, deep learning, and reinforcement learning projects.
  • Ability to identify relevant AI model evaluation metrics and present technical outcomes to technical and non-technical audiences, highlighting business value and ROI.
  • Proficiency in Python and Visual Basic coding.
  • Expert-level knowledge of NumPy, Pandas, scikit-learn, TensorFlow, and Keras.
  • Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.
  • Strong analytical and problem-solving skills.

Responsibilities

  • Develop dynamic process simulation models for various plant scenarios.
  • Analyze historian data, perform exploratory data analysis, and preprocess data.
  • Implement AI projects from data ingestion and feature engineering through model deployment and monitoring.
  • Advocate best practices in data analysis, data preprocessing, and machine learning model development.
  • Partner with domain experts, process engineers, and project managers to translate operational challenges into AI-driven solutions.
  • Present technical outcomes to technical and non-technical audiences, highlighting business value and ROI.
  • Implement classical machine learning techniques to prepare soft sensors and reinforcement learning models for autonomous process-plant control.
  • Design and develop AI models to troubleshoot plant upsets and support asset performance management across maintenance strategies.
  • Use generative AI, large language models, and deep reinforcement learning to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior.
  • Ensure AI models are scalable and deployable within industrial platforms, integrating with PLC, DCS, SCADA, historians, EAM, MES/MOM, SCM, and ERP systems.
  • Ensure compliance with ethical AI principles, including fairness, transparency, and bias mitigation.

Desired Qualifications

  • Project delivery experience in the oil and gas industry.

About the Company

Yokogawa

Industrial automation and process control solutions

Yokogawa provides industrial automation, measurement, and IT solutions for industries such as oil and gas, chemicals, and power. Its products connect operations technology with information technology, using sensors, field instruments, and control systems to enable real-time monitoring, optimization, and predictive maintenance across devices, edge systems, and cloud platforms. The company differentiates itself through a long history in process control, a broad end-to-end portfolio under the OpreX brand, and active digital transformation efforts that integrate IIoT, AI, and digital twins, often in partnerships with Microsoft for Azure and cybersecurity. Its goal is to help customers run safer, more efficient, and more sustainable operations by advancing from automation to autonomy with data-driven, enterprise-scale solutions.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Tokyo, Japan
Founded
1915

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