At a Glance
- Tasks: Design and run AI-accelerated simulations in physics and engineering.
- Company: Join Mistral AI, a pioneering company transforming the future of AI.
- Benefits: Competitive salary, equity, health insurance, and hybrid work model.
- Other info: Work in dynamic locations like Munich, Paris, and London with excellent career growth.
- Why this job: Make a meaningful impact with cutting-edge AI technology in a collaborative environment.
- Qualifications: PhD in physics or engineering with 5+ years of industry experience.
About Mistral
At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. 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 France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact.
About The Job
Mistral AI is looking for Applied Scientists with deep domain and industrial expertise in physics and engineering sciences to work at the frontier of AI-accelerated simulation. You will work with industrial customers and internal research teams to build and deploy AI Physics Models alongside our existing offerings of Large Language Models. You will contribute across the full stack: leveraging your deep domain expertise to understand complex problems that will be tackled with frontier AI. Curating high-fidelity simulation datasets, training and evaluating models, and delivering production-grade AI solutions directly to engineering teams. Target domains include computational fluid dynamics, structural mechanics, semiconductor design, multi-physics modelling, and digital twins. Working cross-functionally with research, product, and customer-facing teams, you will ensure our models meet real engineering standards, not just benchmark metrics.
What You Will Do
- 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
- Collaborate closely 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
About You
- Fluent English with excellent communication skills - able to explain technical simulation concepts to both engineering and non-technical audiences
- Have a PhD in physics or engineering and 5 years+ of industry experience in a relevant domain. You work in a key engineering industry: Automotive, Aerospace or Semiconductors and have an interest in machine learning
- 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
It would be great if
- Have a deep passion for machine learning
- 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
- Locations: Munich, Paris, London, Amsterdam, Lausanne, Linz. Hybrid work model.
- 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
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Applied Scientist / Domain Expert, AI4Engineering - EMEA employer: Mistral AI
Mistral AI is an exceptional employer that champions innovation and collaboration in the field of AI, particularly within the engineering domain. With a dynamic work culture that values creativity and low-ego teamwork, employees benefit from competitive salaries, equity options, and comprehensive health insurance, alongside generous parental leave and hybrid working arrangements. Located in vibrant cities like Munich, Paris, and London, Mistral offers unique opportunities for professional growth and the chance to make a meaningful impact in AI-accelerated simulation.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist / Domain Expert, AI4Engineering - EMEA
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Mistral AI!
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✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Mistral AI.
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When you find a suitable opening like Applied Scientist / Domain Expert, AI4Engineering - EMEA at Mistral AI, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Applied Scientist / Domain Expert, AI4Engineering - EMEA
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Mistral AI, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Mistral AI. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Mistral AI
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Mistral AI!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
