At a Glance
- Tasks: Architect and execute cutting-edge simulation workflows for AI-driven physics models.
- Company: Pioneering startup reshaping engineering with Foundational AI models.
- Benefits: Full ownership of data strategy, high impact projects, and elite team collaboration.
- Other info: Dynamic environment with opportunities to work on world-class engineering challenges.
- Why this job: Join us to revolutionise engineering and make a real difference in sustainable transport.
- Qualifications: Postgraduate degree in relevant fields and deep CFD mastery required.
The predicted salary is between 36000 - 60000 € per year.
BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow, and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world’s hardest physical engineering challenges in automotive, aerospace, and energy.
We are looking for a Simulation Engineer who views CFD not just as a validation tool, but as the high-fidelity engine that powers the next generation of generative physics.
The Role
As a Simulation Engineer, you are the guardian of the ground truth. This is not a "black box" simulation role; you will architect the end-to-end data pipelines that feed our AI models. You will be responsible for generating the high-fidelity, transient CFD datasets that allow our models to learn the fundamental laws of fluid dynamics. You will work at the intersection of classical physics and cutting-edge AI, collaborating with global OEMs, Formula 1 teams, and aerospace innovators to ensure our training data is robust, repeatable, and production-ready.
Key Responsibilities
- Architect CFD-to-ML Pipelines: Design and execute end-to-end simulation workflows—from CAD cleanup and surface triangulation to volume meshing and solver execution—specifically optimized for AI training at scale.
- High-Fidelity Data Generation: Develop and validate transient CFD datasets (RANS/URANS/HRLES) that serve as the "gold standard" for our foundational models, ensuring they reflect real-world physical complexity.
- Physics-ML Integration: Collaborate deeply with AI researchers to translate fluid dynamics principles into model constraints and validation criteria. You will ensure our AI doesn’t just "look" right, but is physically accurate.
- Drive Simulation Automation: Transition beyond manual setups by building automated, scalable meshing and solver infrastructures that reduce turnaround time without sacrificing scientific rigor.
- Customer-Centric Engineering: Work directly with technical partners in F1 and Aerospace to align simulation parameters with industrial-scale design challenges.
- Quality & Reproducibility: Establish the company-wide standards for mesh quality, solver settings, and simulation fidelity to ensure every byte of data we generate is of world-class quality.
About You
You have a "founder’s mentality"; you are a builder who is comfortable being the first to tackle a problem and the one to build the system that solves it. You are passionate about fluid dynamics but frustrated by the slow pace of traditional tools, and you are eager to use your expertise to help build a faster, AI-driven future.
Essential Requirements
- Postgraduate Degree (MSc/PhD) in Aerospace, Aeronautical, Mechanical Engineering, or Mathematics.
- Deep CFD Mastery: Extensive experience with industry-standard solvers and mesh generation (OpenFOAM, ANSYS Fluent, STAR-CCM+, ANSA, or ParaView).
- Fluid Dynamics Expert: Strong theoretical background in incompressible/compressible flow, turbulence modeling (RANS, LES, HRLES, etc), and heat transfer.
- Hands-on Builder: Proven ability to take a project from a raw CAD file to a fully validated, post-processed simulation.
- Communicator: Ability to bridge the gap between classical engineering disciplines and modern machine learning teams.
Highly Desirable
- Sci-ML Curiosity: Prior experience or a strong interest in CFD-ML, Scientific Machine Learning, or surrogate modeling.
- Scripting & Automation: Proficiency in Python or C++ to automate simulation workflows and data extraction.
- HPC Experience: Experience running large-scale simulations on high-performance compute clusters or cloud infrastructure.
Why Join Us?
- Full Ownership: You will own the data strategy that defines the accuracy of our foundational models.
- High Impact: Your simulations will directly train the AI that will design the next generation of sustainable transport and energy systems.
- Elite Team: Work alongside veterans from world-leading AI labs and top-tier engineering teams in a culture of "impact with integrity."
Simulation Engineer in London employer: BeyondMath
BeyondMath is an exceptional employer for Simulation Engineers, offering a unique opportunity to work at the forefront of AI-driven engineering in a dynamic startup environment. With a strong focus on innovation and collaboration, employees benefit from full ownership of their projects, access to elite teams, and the chance to make a significant impact on sustainable transport and energy systems. The company fosters a culture of integrity and growth, ensuring that every team member can thrive while tackling some of the world's most challenging physical engineering problems.
StudySmarter Expert Advice🤫
We think this is how you could land Simulation Engineer in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the aerospace and automotive sectors, especially those who work with CFD. Attend industry events or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your CFD projects and simulations. Use platforms like GitHub to share your code and results. This not only demonstrates your expertise but also gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your fluid dynamics knowledge and simulation techniques. Practice explaining complex concepts in simple terms, as you’ll need to communicate effectively with both engineering and AI teams. Mock interviews can help you nail this!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate Simulation Engineers who want to make an impact. Tailor your application to highlight how your skills align with our mission at BeyondMath, and let’s reshape engineering together!
We think you need these skills to ace Simulation Engineer in London
Some tips for your application 🫡
Show Your Passion for Fluid Dynamics:When writing your application, let us see your enthusiasm for fluid dynamics shine through! Share specific examples of projects or experiences that highlight your expertise and how they relate to the role of a Simulation Engineer.
Be Clear and Concise:We appreciate clarity! Make sure your application is well-structured and to the point. Use bullet points where necessary to make it easy for us to see your qualifications and experience at a glance.
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the key responsibilities and requirements mentioned in the job description. Show us how your skills align with what we’re looking for in a Simulation Engineer.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at BeyondMath
✨Know Your CFD Inside Out
Make sure you brush up on your computational fluid dynamics (CFD) knowledge. Be ready to discuss specific solvers like OpenFOAM or ANSYS Fluent, and how you've used them in past projects. This will show that you're not just familiar with the tools, but that you can leverage them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex engineering challenges. Think about a project where you had to transition from a raw CAD file to a validated simulation. Highlight your thought process and the steps you took to ensure accuracy and efficiency.
✨Bridge the Gap Between Physics and AI
Since this role involves collaboration with AI researchers, be ready to discuss how you can integrate fluid dynamics principles into machine learning models. Bring examples of how you've worked at the intersection of these fields, and how you can contribute to making simulations more accurate.
✨Demonstrate Your Automation Skills
If you have experience with scripting in Python or C++, make sure to mention it. Talk about any automation workflows you've built to streamline simulation processes. This will show that you're not only a hands-on builder but also someone who can enhance productivity through technology.
