---
title: 'AI Scientist - Domain Expert Crashworthiness at Mistral'
canonical: 'https://feeny.ai/job/ai-scientist-domain-expert-crashworthiness-mistral-paris-hzv87skvyv04'
type: 'job'
last_seen: '2026-11-01'
---

# AI Scientist - Domain Expert Crashworthiness at Mistral

- **Company:** [Mistral](https://feeny.ai/companies/mistral)
- **Location:** Paris, France
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-10-30
- **Last confirmed live:** 2026-11-01
- **Apply:** https://jobs.ashbyhq.com/mistral.ai/bc659575-b7c2-406c-825b-fdd58c503594

## Job description

## About Mistral

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

## About the job

Mistral AI is looking for a Domain Expert in crashworthiness simulations to help build AI-accelerated simulation capabilities for industrial engineering. You will work at the intersection of industrial simulation, physics modeling, machine learning, and engineering workflows. Your role is to bring deep solid-mechanics expertise into the design, training, evaluation, and deployment of AI Physics Models for real engineering use cases. This is a hands-on technical role. We are looking for someone who understands industrial structural simulation not only conceptually, but through direct experience with simulation models, solver workflows, data generation, validation, and engineering decision-making. You will work with research, product, and customer-facing teams to ensure that our models are useful against real engineering standards — not only benchmark metrics. Relevant application areas may include automotive crashworthiness, aerospace structures, consumer-electronics drop/reliability, manufacturing, durability/fatigue, and other nonlinear structural mechanics problems.

## What you will do

- Work with our research team to define, generate, and iteratively improve simulation datasets for training and evaluating crashworthiness foundation models, balancing coverage of relevant physical scenarios, simulation fidelity, and computational cost.
- Design and run high-fidelity simulation campaigns using structural mechanics solvers such as Abaqus, LS-DYNA, Ansys Mechanical, Radioss or equivalent tools.
- Define the relevant variation space for training data: geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs.
- Build or guide automated pipelines for simulation setup, execution, post-processing, dataset creation, and model evaluation.
- Work with research teams to train and evaluate AI models on simulation data, and diagnose failure modes caused by data gaps, poor coverage, numerical artifacts, or model limitations.
- Evaluate model outputs against industrial engineering needs, including field-level accuracy, scalar KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior.
- Work with industrial customers to understand their simulation workflows and engineering priorities, define use cases and success criteria, and incorporate their feedback into model development and validation.

## About you

- You have deep expertise in crashworthiness, solid mechanics, and structural mechanics, with substantial experience in industrial simulation workflows.
- You have a Master’s degree or equivalent technical depth in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related field.
- You have 4+ years of relevant industrial experience (or PhD +1 years) in domains such as automotive, aerospace, and consumer electronics.
- You have hands-on experience with explicit dynamics for crash or impact simulation and understand nonlinear FEM and related topics such as contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability.
- You have direct experience with simulation validation, correlation, model quality, numerical sensitivity, and engineering KPI definition.
- You are a strong Python developer who can build and maintain reliable tools for simulation automation, data processing, and model evaluation. You apply sound software engineering practices, including version control with Git, automated testing, code review, and clear documentation.
- You have hands-on experience working in Linux and HPC environments, including submitting and monitoring batch jobs, selecting appropriate compute resources, and troubleshooting simulation workflows. You can run simulation campaigns efficiently across a compute cluster.
- You are comfortable operating in ambiguous technical environments and turning poorly defined industrial problems into scoped datasets, experiments, metrics, and execution plans.
- You communicate clearly with both deep technical experts and non-specialist stakeholders.

It would be great if you

- Have experience applying machine learning, surrogate modeling, reduced-order modeling, optimization, or data-driven methods to simulation problems.
- Have contributed to reusable internal tools, open-source code, simulation automation frameworks, or production-quality engineering workflows.
- Have experience working directly with industrial customers, product teams, or engineering decision-makers.
- Have publications, patents, internal technical leadership, or recognized contributions in engineering, simulation, computational mechanics, or ML-for-physics communities.

## What We Offer

We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our [Benefits page](https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link).

Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our [Applicant Privacy Policy](https://legal.mistral.ai/terms/applicant-privacy-policy).

## About Mistral

## Company Overview
- **One-liner**: Mistral is a French AI company building open, frontier-grade large language models, developer platforms, and applied AI solutions for enterprises and governments.
- **Entity Type**: Private (Series C)
- **Headquarters**: Paris, France (15 rue des Halles)
- **Founded**: April 2023
- **Founders**: Arthur Mensch (CEO), Guillaume Lample (Chief Science Officer), Timothée Lacroix (CTO)

## Core Business
- **Primary industry/industries**: Artificial Intelligence, Large Language Models, Enterprise AI Software
- **Target customers**: B2B, Enterprise, Government, and Developers (B2D)
- **Mission or purpose statement**: "To make frontier AI open to all, and together solve the world's hardest problems."

## Products & Services
- **Mistral Large**: Frontier-grade large language model for complex reasoning and enterprise tasks.
- **Mistral Small 3**: Efficient, lightweight model for cost-sensitive deployments.
- **Mistral Code / Vibe**: AI agent for long-horizon, autonomous software development and task completion.
- **Le Chat**: Consumer-facing AI assistant and chatbot.
- **Mistral OCR 4**: State-of-the-art document intelligence model for extracting and understanding text from images and PDFs.
- **Mistral Forge**: Custom model development service for training, aligning, and evaluating proprietary AI models on private data.
- **Mistral Studio**: Platform for building, testing, and running AI agents and applications with full control.
- **Mistral Compute**: Infrastructure and orchestration platform for frontier-scale training and inference (edge to cloud).
- **Mistral Search Toolkit**: Tools for integrating search and retrieval into AI applications.
- **Voxtral**: Voice AI model for speech-based interactions.

## Market Standing
- **Valuation/Market Cap**: $4.016 billion (latest reported valuation, per CB Insights; date not specified but likely post-Series C)
- **Key Metric**: Total funding raised across Seed, Series A, Series B, and Series C rounds (specific amounts not disclosed in search results).
- **Notable Investors/Partners**: Not explicitly named in search results, but the company partners with organizations in finance, manufacturing, defense, energy, and the public sector.
- **Growth Signals**: 
  - Rapid scaling: 900+ employees across 30+ nationalities as of mid-2026.
  - 50% of leadership roles held by women.
  - Key product launches on a near-monthly cadence (e.g., Mistral OCR, Forge, Vibe, Compute, Search Toolkit, Voxtral).
  - Strong presence in high-stakes, regulated industries (defense, energy, public sector).

## Competitive Advantages
- **Open-source DNA**: Commitment to openness, transparency, and cost efficiency differentiates Mistral from closed, Big Tech AI labs.
- **Full-stack ownership**: Controls the entire stack from frontier models to developer tools, applications, and compute infrastructure, enabling deep customization and reliability.
- **European leadership**: Positioned as a sovereign, European AI champion, appealing to governments and enterprises seeking data control and regulatory compliance.
- **Speed and rigor**: Culture of rapid experimentation, iteration, and data-driven decision-making.

## Strategic Focus
- **Enterprise and government partnerships**: Co-creating tailored AI systems for mission-critical use cases in finance, manufacturing, defense, energy, and public sector.
- **Open platform ecosystem**: Expanding Mistral Studio and Forge to enable customers to build custom models and agents on their own data.
- **Infrastructure as a product**: Commercializing Mistral Compute to become a platform for others to train and run AI workloads.
- **Continuous model innovation**: Releasing new frontier models and capabilities (OCR, voice, code agents) at a rapid pace.

## Why Work Here
- **Culture**: Flat structure, high ownership, low ego, and a "builders, not order takers" mentality. The company values audacity, speed, rigor, and customer centricity.
- **Remote/Hybrid/Office**: Based in Paris (15 rue des Halles); relocation support and visa sponsorship offered. Specific remote/hybrid policy not detailed, but global team suggests flexibility.
- **Notable perks and benefits** (from careers page):
  - 20 weeks paid parental leave for all birthing parents.
  - 100% employer-sponsored medical, dental, and vision coverage for employees and dependents.
  - 6% 401k match (US) / 5% pension contribution (UK).
  - Childcare support (reserved daycare seats or financial assistance).
  - Meal allowances and transportation support.
  - Fitness and wellness subsidies.
  - Relocation and settling-in services.
  - Financial and career planning support.
- **Team composition**: 900+ employees from 30+ nationalities; 50% female leaders.
- **Interview process**: For science, product, and engineering roles: intro conversation → 2-5 technical exercises → 1-3 interviews (hiring manager + teammates) → values conversation → reference checks.

## Sources
1. [Mistral AI - About Page](https://mistral.ai/about/)
2. [Mistral AI - Careers Page](https://mistral.ai/careers/)
3. [Mistral AI - Homepage](https://mistral.ai/)
4. [CB Insights - Mistral AI Company Profile](https://www.cbinsights.com/company/mistral-ai)
5. [Mistral AI - LinkedIn](https://www.linkedin.com/company/mistralai)

## Other roles at Mistral

- [Customer Success, EMEA](https://feeny.ai/job/customer-success-emea-mistral-paris-45esj6zs38ex) — Paris, France
- [Research Engineer,  Robotics](https://feeny.ai/job/research-engineer-robotics-mistral-paris-b77xhk57pb9r) — Paris, France
- [Applied Science - Time Series](https://feeny.ai/job/applied-science-time-series-mistral-paris-1kmf0pwvvgz7) — Paris, France
- [Applied Science - Cybersecurity](https://feeny.ai/job/applied-science-cybersecurity-mistral-paris-83v2sybrm04w) — Paris, France
- [Account Executive, Enterprise, Swiss Romande](https://feeny.ai/job/account-executive-enterprise-swiss-romande-mistral-zurich-nh19rcxkzaqp) — Zurich, Switzerland
- [Engineering Manager, Sandbox](https://feeny.ai/job/engineering-manager-sandbox-mistral-paris-5wx65405emb2) — Paris, France
- [Engineering Manager, Storage](https://feeny.ai/job/engineering-manager-storage-mistral-paris-ekf23bqg33ar) — Paris, France
- [Engineering Manager, Fleet Delivery](https://feeny.ai/job/engineering-manager-fleet-delivery-mistral-paris-zsspnkk7y0k5) — Paris, France
- [Engineering Manager, Serverless Containers](https://feeny.ai/job/engineering-manager-serverless-containers-mistral-paris-m06we4kkhq7s) — Paris, France
- [People Tech & Analytics Engineer](https://feeny.ai/job/people-tech-analytics-engineer-mistral-paris-1mbgsk5j3gj7) — Paris, France