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.