Industrial ML Engineer: Physics‑Informed AI for Factory Ops

EntroMetrix; Greater London; On-site; GBP 65,000 - 95,000; Full time

Benefits offered by this job

Unlimited coffee

Competitive compensation package

London office

Job summary

EntroMetrix is building physics-informed AI to help industrial teams run more efficient and resilient operations from its London office. We seek a hands-on Machine Learning Engineer to design, train and deploy models that handle messy real-world data and respect physical constraints.

You will work with our founding team, customer sites and industrial data to turn early validation into a scalable product, training end-to-end systems and contributing to platform direction.

Qualifications

• Degree in machine learning, computer science, engineering, physics or related STEM field from a world-leading university (PhD-level).
• Strong practical experience building ML models in Python, preferably with PyTorch or JAX.
• Experience with scientific ML, time-series modelling, optimisation, simulation or probabilistic modelling.

Responsibilities

• Design, train and deploy ML 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/operational constraints.
• Develop reusable modelling components scalable across sites and use cases.
• Collaborate with product/engineering to move models from prototype to production.
• Evaluate model performance, reliability and robustness in applied settings.
• Engage with customers to understand operational context behind the data.
• Help define the technical direction of the platform as an early ML hire.

Skills

Python

PyTorch

JAX

Time-series modelling

Physics-informed ML

Education

PhD in ML/CS/Engineering/Physics

Tools

PyTorch

JAX

Job description

EntroMetrix is building physics-informed AI to help industrial teams run more efficient and resilient operations from its London office. We seek a hands-on Machine Learning Engineer to design, train and deploy models that handle messy real-world data and respect physical constraints.

You will work with our founding team, customer sites and industrial data to turn early validation into a scalable product, training end-to-end systems and contributing to platform direction.