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.

• 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.

• 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.

• 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.