Machine Learning Engineer, Turbulent Flow

EntroMetrix builds physics-informed AI to help industrial teams operate more efficiently, resiliently, and sustainably. The Machine Learning Engineer will design, train, deploy, and evaluate models for complex operational systems using scientific machine learning, time-series modelling, optimisation, and real-world industrial data. The role also involves moving models from prototype to production, working with customers, and contributing to the technical direction of the platform.

Responsibilities:

• Design, train and deploy machine learning models for complex operational systems
• Work with sparse, noisy and irregular time-series data from real-world environments
• Build models that combine data-driven learning with physical and operational constraints
• Develop reusable modelling components that can scale across different sites and use cases
• Work with the product and engineering team to move models from prototype to production
• Evaluate model performance, reliability and robustness in applied settings
• Spend time with customers to understand the operational context behind the data
• Contribute to the technical direction of the platform as one of the first ML hires