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.