AI​/ML Engineer

Yokogawa, award winner for ‘Best Asset Monitoring Technology’ and ‘Best Digital Twin Technology’ at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services across multiple industries. We aim to shape a better future by supporting the energy transition, (bio) technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by leveraging our ability to measure and connect.

Our 18,000 employees work in over 60 countries with one corporate mission: ‘co-innovate tomorrow’. We value respect, value creation, collaboration, integrity, and gratitude, and offer career opportunities in a truly global culture.

We are looking for an AI/ML Engineer with deep technical expertise and proven leadership in delivering impactful solutions for the oil & gas industry. In this role, you will design, develop, and implement advanced AI/ML models, working closely with cross-functional teams to optimize operations and deliver data-driven insights in challenging industrial environments.

• Develop dynamic process simulation models to simulate various plant scenarios.
• Conduct exploratory data analysis, data preprocessing, and make intelligent recommendations.
• Implement classical machine learning techniques to develop soft sensors and reinforcement learning models for process plant autonomous control operations.
• Design and develop AI models that troubleshoot plant upsets and support asset performance management across various maintenance strategies.
• Leverage generative AI (large language models, 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, focusing on fairness, transparency, and bias mitigation.

• Lead development of dynamic process simulation models for various plant scenarios.
• Analyze data historians and perform exploratory data analysis and preprocessing.
• Manage end-to-end AI projects from data ingestion, feature engineering, to model deployment and monitoring.
• Advocate best practices in data analysis, pre-processing, 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 both technical and non-technical audiences, highlighting business value and ROI.

• Bachelor’s or master’s degree in chemical engineering, AI, machine learning, or related field.
• 6+ years of hands‑on experience in AI/ML and process simulation project execution.
• Proven project delivery experience in industrial or energy sectors, preference for oil & gas.
• Demonstrated knowledge of oil & gas processes (upstream, midstream, downstream), instrumentation, and control systems.
• Experience developing process dynamic simulations using PFDs and P&IDs and troubleshooting.
• Proficiency in handling large-scale, time-series, and sensor/IoT data within industrial contexts.
• Familiarity with real-time data challenges and solutions in high-stakes industrial environments.
• Strong foundation in machine learning algorithms (supervised, unsupervised, reinforcement learning), statistical modelling, and optimization techniques.
• Experience with classical machine learning, deep learning, and reinforcement learning projects.
• Ability to identify relevant metrics for AI model evaluation.
• Strong analytical, problem-solving, and communication skills, and proven ability to work across teams.

• Languages:
  
  Proficiency in Python and Visual Basic.
• ML Libraries:
  Expert-level knowledge of Num Py, Pandas, Scikit-learn, Tensor Flow, and Keras.

• Experience integrating AI/ML solutions into existing industrial control systems and operational dashboards.

• Demonstrated exceptional technical…