Artificial Intelligence Scientist

• Translate industrial and process-related problems into mathematical optimization, machine learning, or artificial intelligence solutions
• Formulate and solve mathematical optimization problems, including linear, mixed-integer, nonlinear, and constraint programming
• Design and develop machine learning models applied to the control and operation of industrial processes
• Develop solutions based on historical process data to automatically improve the performance of control loops and control strategies
• Develop LLM-based artificial intelligence agents to support engineering activities and the operation of control systems
• Prepare process data, including collection, cleaning, synchronization, and the handling of time series, outliers, and missing data
• Develop feature engineering processes for model training
• Define and implement model training, validation, and deployment pipelines with software and data teams
• Support the integration of algorithms into the area's products in collaboration with the software development team
• Conduct proof-of-concept projects for algorithms and solutions in real-world plants
• Prepare configuration and usage documentation for non-specialist professionals
• Research new optimization, machine learning, and artificial intelligence technologies for current and future products

• Advanced English proficiency
• Ability to translate industrial and process-related problems into optimization, machine learning, and artificial intelligence solutions
• Strong knowledge of mathematical optimization and problem formulation, including linear programming, mixed-integer programming, nonlinear programming, and constraint programming
• Experience with solvers and modeling languages such as Gurobi, CPLEX, OR-Tools, or Pyomo
• Strong knowledge of machine learning, including supervised and unsupervised learning, neural networks, model validation, and model evaluation
• Experience in data preparation and feature engineering, with an emphasis on time series processing and modeling
• Understanding of data pipelines for model training, validation, and deployment
• Proficiency in Python and data science, machine learning, and optimization libraries such as NumPy, pandas, scikit-learn, and PyTorch
• Clear and objective communication skills, with the ability to work in multicultural teams
• Willingness and ability to continuously learn and stay current with innovations and trends
• Strong interpersonal and collaboration skills, with the ability to work smoothly and effectively as part of a team, either on-site or remotely
• Systems and strategic thinking, analytical mindset, results orientation, discipline, and innovation
• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• Preferred qualifications: process automation and control, industrial processes, C#/.NET, Git, SQL, LLM/RAG agents, reinforcement learning, metaheuristics, Bayesian optimization, and MLOps practices