AI Physics Scientist - Simulation & ML for Engineering

Mistral Ai; Paris; Sur place; EUR 95 000 - 150 000; Plein temps

Résumé du poste

Mistral AI seeks Applied Scientists to advance AI-Physics models bridging simulation and machine learning. You will curate high-fidelity datasets, train and evaluate models, and deploy production-grade AI solutions for engineering teams across domains like CFD, structural mechanics, and semiconductor design.

You will work cross-functionally with research, product, and customer-facing teams to ensure models meet engineering standards and real-world usage.

Qualifications

• Fluent English with excellent communication skills.
• PhD or Master's in AI or an engineering science (Mechanical Eng., Electrical Eng., CFD, Structural Mechanics, Semiconductor Eng., or related).
• Solid understanding of deep learning and engineering or physics.
• Comfortable with PyTorch or JAX for implementing and training models.
• Clean, readable Python code; Linux/HPC experience.
• Self-directed; proactive problem solver.
• Evidence of industrial projects, academic work, or personal projects.

Responsabilités

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

Connaissances

Fluent English

PyTorch

JAX

Python

Linux/HPC

Self-directed

Formation

PhD or Master's in AI or an engineering science

Outils

PyTorch

JAX

Description du poste

Mistral AI seeks Applied Scientists to advance AI-Physics models bridging simulation and machine learning. You will curate high-fidelity datasets, train and evaluate models, and deploy production-grade AI solutions for engineering teams across domains like CFD, structural mechanics, and semiconductor design.

You will work cross-functionally with research, product, and customer-facing teams to ensure models meet engineering standards and real-world usage.