Job Description

AI Engineer – Hybrid Models & Process Digital TwinsRole Overview

The AI Engineer will design and implement hybrid models that combine first-principles (physics-based) modeling with deep learning, enabling process digital twins and AI agents for advanced simulation, optimization, and autonomous decision-making in industrial environments, mainly Oil & Gas Industry.

Key Responsibilities
  • Develop hybrid physics-informed (first principles) and data-driven (Neural Networks and others) models.
  • Build and deploy deep learning models for industrial process applications.
  • Implement and maintain process digital twins using real-time and historical data.
  • Design AI agents that use digital twins for optimization and decision support.
  • Integrate AI solutions with existing industrial and cloud systems.
  • Ensure model robustness, validation, and lifecycle management.
Core Requirements
  • Engineering degree (Chemical, Systems, Electrical, Mechanical, or related).
  • Strong expertise in deep learning and neural networks.
  • Experience with first-principles / physics-based modeling.
  • Advanced Python programming skills.
  • Experience with process modeling or digital twins.
  • Working knowledge of AI agents and autonomous systems.
Nice to Have
  • Industrial experience (energy, oil & gas, chemicals, manufacturing).
  • Knowledge of optimization, control, or MPC (Multivariate Model Predictive Process Control)
  • Experience with MLOps, Docker, and cloud platforms.
  • Familiarity with multi-agent architectures.

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