Machine Learning Engineer
BeyondMathGenerative Physics company
London, United KingdomMid
Insight Partners
Acrew Capital
Cambridge Innovation Capital
UP.Partners
InMotion Ventures
Builders VC
Data & AI
About the role
TL;DR
Develop and optimize AI models for physics simulation in a pioneering startup.
- •As a Machine Learning Engineer, you'll contribute to core model development, shaping model architecture, and delivering performant systems for our Generative Physics simulation platform.
- •Key Responsibilities Design and train deep learning models for physics simulation.
- •Drive optimization efforts for model inference speed, accuracy, and robustness.
- •Research effective ways to represent geometric design variations for efficient use by machine learning models.
- •Partner with engineering teams to deploy and monitor models in production-grade pipelines.
- •Contribute to design decisions around model and data architecture, tooling, and ML infrastructure.
- •Requirements Strong track record applying ML to complex real-world problems.
- •Deep understanding of machine learning theory, including optimization, generalisation, and various model architectures.
- •Strong python skills and experience with deep learning libraries (TensorFlow/PyTorch/JAX).
- •Ability to clearly explain complex ML concepts and research findings to both technical and non-technical audiences.
- •Master's Degree (PhD preferred) in Machine Learning, Computer Science, or a related quantitative field.
Required skills
PythonTensorFlowPyTorchscikit-learn
Domain expertise
aerospaceautomotive
Tech stack
PythonTensorFlowPyTorchJAXPostgreSQLAWS