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Machine Learning Engineer

Platform Recruitment· London Area, United Kingdom· Up to £120,000/yrSponsorship
Posted 10 Aug 2026 · Added 10 Aug 2026, 16:57
Platform RecruitmentIT servicesfounded 2010
AI summary

You'll use Python, PyTorch, TensorFlow, or JAX to deploy and monitor production-grade ML pipelines. The role builds foundational AI models that replace traditional physics simulation for automotive, aerospace, and energy challenges. You'll contribute to core model development and architecture decisions alongside ML researchers and engineers.

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Job Title: Machine Learning Engineer, Physics AI

Location: London

Salary: Up to £100,000 DOE

A VC-backed AI startup is looking for a Machine Learning Engineer to help build foundational AI models that replace traditional physics simulation methods. The company is working on some of the hardest physical engineering challenges in automotive, aerospace, and energy, delivering AI that rivals simulation accuracy at orders of magnitude higher speed.

This is not a generic ML role. You will be working at the intersection of ML research and engineering, contributing to core model development, shaping architecture decisions, and deploying performant systems into real-world design optimisation workflows. You will work closely with ML researchers, software engineers, and industry partners on problems that have direct industrial and environmental impact.

What we are looking for

MSc or PhD in Machine Learning, Computer Science, or a related quantitative field

Strong track record applying ML to complex real-world problems, ideally involving geometry or physical systems

Deep understanding of ML theory including optimisation, generalisation, and model architectures

Strong Python skills with hands-on experience in PyTorch, TensorFlow, or JAX

Experience deploying and monitoring models in production grade pipelines

Ability to communicate complex ML concepts clearly to both technical and non-technical audiences

Particularly strong candidates will also have

Familiarity with aerodynamic principles or computational fluid dynamics

Experience with physics-informed machine learning or integrating physical constraints into models

Experience with geometry representation for ML, including 3D or mesh-based approaches

Prior experience with design optimisation algorithms in an engineering context

Why this role

You will have direct influence over the architecture and direction of a platform redefining how physical engineering challenges are solved. The team includes veterans from world-leading AI labs and engineering firms, and the work has real-world impact on sustainable energy and efficient transport.

This role requires existing right to work in the UK. Visa sponsorship is not available.

If your background fits, apply below