Data Scientist, Onsite London | AI for Engineering

PhysicsX Ltd.; Greater London; Hybride; GBP 60 000 - 90 000; Plein temps

Avantages offerts par ce poste

Equity options

Pension contribution

Free office lunches

Hybrid work model

25 days Annual Leave

Résumé du poste

PhysicsX Ltd. is seeking a Data Scientist in Delivery based in London, combining AI with engineering simulations. You will work with simulation and ML engineers and customers to transform cutting-edge AI models into practical tools used on-site to solve real engineering challenges.

You’ll handle data preprocessing, model development, and deployment of scalable pipelines, while collaborating across disciplines to ensure impactful results for aerospace, materials, and automotive use cases.

Qualifications

• Strong foundations in data-driven modelling and deep learning.
• Ability to deploy production-ready models and data pipelines.

Responsabilités

• Pre-process and analyse data for predictive modelling.
• Develop and apply deep learning models with optimization methods to predict and control physical systems.
• Ensure quality, accuracy and impact of work.
• Design, build and test scalable data pipelines for production environments.
• Collaborate with Simulation and ML engineers and customers to integrate models with simulations.
• Engage with customers on-site to onboard users and co-develop solutions.

Connaissances

Python

Deep learning

NumPy

Pandas

SciPy

TensorFlow

PyTorch

Probabilistic modelling

Formation

Master's or PhD in a quantitative field

Outils

Docker

Git

Description du poste

PhysicsX Ltd. is seeking a Data Scientist in Delivery based in London, combining AI with engineering simulations. You will work with simulation and ML engineers and customers to transform cutting-edge AI models into practical tools used on-site to solve real engineering challenges.

You’ll handle data preprocessing, model development, and deployment of scalable pipelines, while collaborating across disciplines to ensure impactful results for aerospace, materials, and automotive use cases.