ML Engineer - Physics Simulations | Equity | Hybrid London

DeepRec.ai; Greater London; Hybrid; GBP 100,000 - 140,000; Full time

Job summary

DeepRec.ai in Central London is seeking a Machine Learning Engineer to join an early-stage, VC-backed startup building physics-based AI models. You’ll work across research and engineering on a generative physics simulation platform with a strong emphasis on real-world impact.

The role focuses on designing and training models for physics simulations, optimizing inference speed, and collaborating with engineering teams to deploy production pipelines.

Qualifications

• Experience designing and training ML models for physics simulation.
• Ability to deploy models in production-grade pipelines.
• Strong grounding in ML theory: optimisation and generalisation.
• Experience with geometry or physical systems is a plus.

Responsibilities

• Design and train deep learning models for physics simulation across aerodynamic and engineering domains
• Drive optimisation of model inference speed, accuracy and robustness on large-scale industrial datasets
• Research effective ways to represent geometric design variation for use by ML models
• Partner with engineering teams to deploy and monitor models in production-grade pipelines
• Contribute to decisions on model and data architecture, tooling and ML infrastructure
• Strong track record applying ML to complex real-world problems, ideally involving geometry or physical systems
• Deep grounding in ML theory - optimisation, generalisation, model architectures
• Strong Python skills and hands-on experience with PyTorch, TensorFlow or JAX
• Ability to explain complex ML concepts clearly to technical and non-technical audiences
• Master's degree in ML, Computer Science or a related quantitative field (PhD preferred)

Skills

Python

ML theory

Model deployment

Explain ML concepts

Strong communication

Education

Master's degree in ML/CS or related field

Tools

PyTorch

TensorFlow

JAX

Job description

DeepRec.ai in Central London is seeking a Machine Learning Engineer to join an early-stage, VC-backed startup building physics-based AI models. You’ll work across research and engineering on a generative physics simulation platform with a strong emphasis on real-world impact.

The role focuses on designing and training models for physics simulations, optimizing inference speed, and collaborating with engineering teams to deploy production pipelines.