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# Machine Learning Engineer

- **Company:** EntroMetrix
- **Location:** London, UK
- **Salary:** £50,000.0 - £65,000.0
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Machine Learning, Operational Data Store, Pytorch, Information Technology, Data Analytics, Build Tools, Operational Systems, Machine Learning Operations
- **Published:** May 26, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=e9e6ec1574dd8777

## About the Role

Do you have experience in Python?, * A degree in machine learning, computer science, engineering, physics, mathematics, applied mathematics, operations research or a closely related STEM field from a top university.

 * Strong practical experience building machine learning models in Python, ideally using PyTorch, JAX or similar frameworks.
 * Experience with one or more of: scientific machine learning, physics-informed ML, time-series modelling, optimisation, simulation, forecasting or probabilistic modelling.
 * Comfort working with messy real-world data, including missing values, drift, noise and inconsistent data quality.
 * Interest in applying machine learning to physical systems, industrial operations and real-world optimisation problems.
 * In-person working from our London office, typically 4-5 days per week, with occasional travel to customer sites in the UK

Nice to have:

 * Experience deploying ML models into production.
 * Experience with optimisation, simulation, control systems or operations research.
 * Exposure to industrial or operational data environments.
 * Publications or research experience in scientific ML, machine learning for physical systems or applied optimisation.

## Description

We are looking for a Machine Learning Engineer to help build frontier models to understand and improve complex operational systems. The work sits at the intersection of scientific machine learning, time-series modelling, optimisation and real-world deployment. You will work closely with the founding team, customer sites and industrial data to turn early technical validation into a scalable product.

This is a hands-on engineering role. You will not just train models in isolation. You will build systems that need to work with messy data, operational constraints and real-world environments.

What you will do:

 * 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 hire


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