Applied Scientist: AI for Engineering Simulations

Mistral AI; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Mistral AI is seeking Applied Scientists to work at the frontier of AI-accelerated simulation, building AI Physics Models alongside our existing LLM offerings and collaborating with industrial customers and internal research teams.

You will curate high-fidelity simulation datasets, train and evaluate models, and deliver production-grade AI solutions across domains like computational fluid dynamics, structural mechanics, semiconductor design, multi-physics modelling, and digital twins, ensuring

Qualifications

• PhD or Master’s in AI or engineering science.
• Solid understanding of deep learning and engineering/physics.
• Proficiency in PyTorch or JAX and Python.
• Clear communication with engineering and non-technical audiences.

Responsibilities

• Design and run large-scale simulation campaigns using domain-specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus).
• Train AI models on physics data and evaluate coverage, accuracy, and quality against industry standards.
• Build tools for dataset creation, simulation pipeline management, and model evaluation.
• Develop agents and RAG to integrate LLMs with engineering workflows.
• Collaborate with science/research teams on training and diagnose data-driven issues.
• Manage research projects and client communications with engineering teams.

Skills

Python

PyTorch

JAX

Linux HPC

English

Education

PhD or Master's in AI/Engineering

Tools

OpenFOAM

ANSYS

COMSOL

Abaqus

Job description

Mistral AI is seeking Applied Scientists to work at the frontier of AI-accelerated simulation, building AI Physics Models alongside our existing LLM offerings and collaborating with industrial customers and internal research teams.

You will curate high-fidelity simulation datasets, train and evaluate models, and deliver production-grade AI solutions across domains like computational fluid dynamics, structural mechanics, semiconductor design, multi-physics modelling, and digital twins, ensuring