Applied Scientist / Research Engineer, AI4Engineering

Mistral AI

Applied Scientist at Mistral AI developing AI Physics Models for engineering applications. Collaborating with teams to build high-performance simulations in diverse engineering domains.

Posted 4/30/2026full-timeParis • 🇫🇷 FranceMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

LinuxPythonPyTorch

About the role

Key responsibilities & impact

Design and run large-scale simulation campaigns using domain-specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus)
Run training of AI models on physics data, with rigorous evaluation of coverage, accuracy, and quality against industry validation standards
Build tools and frameworks for automated dataset creation, simulation pipeline management, and model evaluation
Develop agents and RAG that integrate LLMs with engineering simulation workflows
Collaborate closely with the collaborate with the science/research team on training runs and diagnose failure modes arising from data gaps or architecture limitations
Manage research projects and client communications with engineering teams

Requirements

What you’ll need

Fluent English with excellent communication skills - able to explain technical simulation concepts to both engineering and non-technical audiences
PhD or Master's in AI or an engineering science: Mechanical Engineering, Electrical Engineering, Computational Fluid Dynamics, Structural Mechanics, Semiconductor Engineering, or a related field. A solid understanding of deep learning and engineering or physics is a must.
Comfortable with PyTorch or JAX for implementing and training models
You write clean, readable Python code and are comfortable in Linux/HPC environments
Self-directed - you don't need detailed roadmaps to make progress
Low-ego, collaborative, and eager to learn at the intersection of simulation and ML
Demonstrated success through industrial projects, academic work, or personal projects
Have industrial or academic experience with simulation solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus, or equivalent)
Have applied ML methods to simulation or surrogate modelling
Have experience automating large-scale simulation campaigns on HPC clusters
Have contributed to a large open-source or industry codebase
Have publications in engineering or ML venues (NeurIPS, ICLR, etc.)
Love improving existing code by fixing typing issues, adding tests and improving CI pipelines

Benefits

Comp & perks

Competitive cash salary and equity
Daily lunch vouchers
Monthly contribution to a Gympass subscription
Monthly contribution to a mobility pass
Full health insurance for you and your family
Generous parental leave policy
Visa sponsorship
Health insurance
Transportation reimbursement (office parking or £90/month public transport)
£90/month gym membership reimbursement
£200/month meal allowance
Pension plan: SmartPension (5% Employee & 3% Employer)

ATS Keywords

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Hard Skills & Tools

OpenFOAMANSYSCOMSOLAbaqusAI model trainingdeep learningPythonPyTorchJAXHPC

Soft Skills

excellent communication skillsself-directedcollaborativeeager to learnability to explain technical concepts

Certifications

PhD in AIMaster's in engineering science