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Yokogawa

Industrial automation and process control solutions

Senior AI/Machine Learning Engineer

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

About the Job

Requirements

  • A bachelor's or master's degree in chemical engineering, AI, machine learning, or a related field is required.
  • At least 10 years of hands-on experience in artificial intelligence and machine learning, including at least 4 years in a senior or lead role.
  • Project delivery experience in industrial or energy sectors is required; oil and gas experience is preferred.
  • Knowledge of upstream, midstream, and downstream oil and gas processes, instrumentation, and control systems is required.
  • Expertise in developing process dynamic simulations using process flow diagrams and piping and instrumentation diagrams, and troubleshooting, is required.
  • Experience handling large-scale, time-series, and sensor/Internet of Things data in industrial contexts is required.
  • Familiarity with real-time data challenges and solutions in high-stakes industrial environments is required.
  • A strong foundation in supervised, unsupervised, and reinforcement learning algorithms, statistical modeling, and optimization techniques is required.
  • Strong experience with classical machine learning, deep learning, and reinforcement learning projects is required.
  • Ability to identify relevant artificial intelligence model evaluation metrics and present technical outcomes to technical and non-technical audiences, highlighting business value and return on investment, is required.
  • Experience with generative artificial intelligence, retrieval-augmented generation, and vector embeddings for knowledge retrieval and decision-making, and with multi-agent systems for industrial applications, is required.
  • Expertise in cloud-based artificial intelligence deployments using AWS, Azure, or Google Cloud, and in edge artificial intelligence for real-time decision-making, is required.
  • Strong analytical and problem-solving skills, and the ability to work across teams, are required.
  • Proficiency in Python and Visual Basic coding is essential.
  • Expert-level knowledge of NumPy, pandas, scikit-learn, TensorFlow, and Keras is required.
  • Experience integrating artificial intelligence and machine learning solutions into existing industrial control systems and operational dashboards is required.

Responsibilities

  • Develop dynamic process simulation models to simulate various plant scenarios.
  • Conduct exploratory data analysis to analyze trends and patterns, preprocess data, and make intelligent recommendations.
  • Implement classical machine learning techniques to prepare soft sensors and reinforcement learning models for autonomous process plant control operations.
  • Design and develop artificial intelligence models that troubleshoot plant upsets and support asset performance management across maintenance strategies.
  • Use generative artificial intelligence, large language models, and deep reinforcement learning to enable multi-agent systems for collaborative decision-making and autonomous goal-seeking behavior.
  • Ensure artificial intelligence models are scalable and deployable within industrial platforms, integrating with programmable logic controllers, distributed control systems, supervisory control and data acquisition systems, historians, enterprise asset management, manufacturing execution and manufacturing operations management systems, supply chain management, and enterprise resource planning systems.
  • Ensure compliance with ethical artificial intelligence principles, including fairness, transparency, and bias mitigation.
  • Implement artificial intelligence projects from data ingestion and feature engineering through model deployment and monitoring.
  • Lead and mentor a team of process engineers and machine learning engineers.
  • Review process models and guide the team in accurately developing plant scenarios in dynamic simulation models.
  • 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 artificial intelligence-driven solutions.
  • Present technical outcomes to technical and non-technical audiences, highlighting business value and return on investment.
  • Ensure artificial intelligence and machine learning solutions comply with industry regulations, safety standards, and data governance policies.
  • Proactively address risks related to data privacy, model bias, and operational safety.

Desired Qualifications

  • Preference is given to candidates with oil and gas industry experience.

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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