At a Glance
- Tasks: Design and run large-scale AI simulation campaigns for engineering applications.
- Company: Join Mistral, a dynamic team at the forefront of AI innovation.
- Benefits: Comprehensive benefits package including healthcare, wellness programs, and work-life balance support.
- Other info: Collaborative environment with opportunities for growth and learning.
- Why this job: Make a real impact in high-stakes industries with cutting-edge AI technology.
- Qualifications: PhD or Master's in AI or engineering science; strong deep learning and coding skills required.
The predicted salary is between 56700 - 69300 £ per year.
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.
The Role
Mistral AI is looking for Applied Scientists with deep expertise in 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 (LLMs). You will contribute across the full stack: 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
- Develop agents and RAG that integrate LLMs with engineering simulation workflows
- 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
What We're Looking For
- 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
It would be great if you
- 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
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 Benefits page.
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Applied Scientist, AI4Engineering employer: Mistral AI
Mistral AI is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a WAN & Edge Network Automation Engineer to thrive. With a strong emphasis on employee growth, you will have access to continuous learning opportunities and cutting-edge projects that challenge your skills. Located in a vibrant tech hub, the company offers a dynamic work environment where creativity and teamwork are highly valued, ensuring that every team member contributes to meaningful advancements in network automation.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist, AI4Engineering
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Mistral AI or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Mistral AI.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Mistral AI.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Mistral AI that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Applied Scientist, AI4Engineering
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Mistral AI.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Mistral AI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Mistral AI
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Mistral AI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
