Applied Scientist / Research Engineer, Ai4engineering - Emea

Mistral AI Mistral AI · AI Frontier · Paris, France · Solutions

Applied Scientist/Research Engineer at Mistral AI focused on building and deploying AI Physics Models for industrial customers, integrating LLMs with engineering simulation workflows. The role involves curating datasets, training and evaluating models, and delivering production-grade AI solutions.

What you'd actually do

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

Skills

Required

  • PyTorch or JAX
  • Python
  • Linux/HPC environments
  • Deep learning
  • Engineering or physics knowledge
  • Communication skills

Nice to have

  • Simulation solvers (OpenFOAM, ANSYS, COMSOL, Abaqus)
  • ML for simulation/surrogate modeling
  • Automating large-scale simulation campaigns on HPC
  • Open-source/industry codebase contribution
  • Publications in engineering or ML venues
  • Improving existing code (typing, tests, CI)

What the JD emphasized

  • deep expertise in engineering sciences
  • AI Physics Models
  • Large Language Models (LLMs)
  • engineering standards
  • rigorous evaluation
  • automated dataset creation
  • simulation pipeline management
  • model evaluation
  • integrate LLMs with engineering simulation workflows
  • diagnose failure modes
  • technical simulation concepts
  • deep learning and engineering or physics is a must
  • Python code
  • Linux/HPC environments
  • industrial projects
  • simulation solvers
  • applied ML methods to simulation
  • automating large-scale simulation campaigns
  • publications in engineering or ML venues

Other signals

  • AI Physics Models
  • AI-accelerated simulation
  • integrate LLMs with engineering simulation workflows