Machine Learning Engineer

Machine Learning Engineer | Central London (3 days/week) | £100k–£140k + Equity DOEWe're working with a VC-backed deep tech startup building foundational AI models for physics - replacing slow, expensive numerical simulation with AI that matches traditional accuracy at orders of magnitude faster speed. The problems are real-world and hard: aerodynamics, CFD, electromagnetics and mechanics, applied across automotive, aerospace and energy - sectors still running on decades-old simulation tooling that's ripe for disruption. They've just closed a strong pre-seed round backed by top-tier VCs and are assembling an early team alongside veterans from world-leading AI labs and engineering firms, working directly with industry partners rather than in the abstract.As Machine Learning Engineer, you'd sit right at the centre of their Generative Physics simulation platform, working across both research and engineering.ResponsibilitiesDesign and train deep learning models for physics simulation across aerodynamic and engineering domainsDrive optimisation of model inference speed, accuracy and robustness on large-scale industrial datasetsResearch effective ways to represent geometric design variation for use by ML modelsPartner with engineering teams to deploy and monitor models in production-grade pipelinesContribute to decisions on model and data architecture, tooling and ML infrastructureEssential requirementsStrong track record applying ML to complex real-world problems, ideally involving geometry or physical systemsDeep grounding in ML theory - optimisation, generalisation, model architecturesStrong Python skills and hands-on experience with PyTorch, TensorFlow or JAXAbility to explain complex ML concepts clearly to technical and non-technical audiencesMaster's degree in ML, Computer Science or a related quantitative field (PhD preferred)Highly desirableFamiliarity with aerodynamics or CFDExperience with optimisation algorithms in an engineering design contextExperience integrating physical laws or constraints into ML modelsWhy joinA direct seat at the table shaping a company aiming to redefine an entire industryWork that feeds directly into the transition to sustainable energy and more efficient transportA small, high-calibre team culture built around "impact with integrity"