Développe des modèles d'intelligence artificielle pour simuler des phénomènes physiques et accompagner la conception industrielle.
Simulation Engineer
BeyondMath recherche un Simulation Engineer pour concevoir des pipelines CFD et produire des jeux de données haute fidélité destinés à l’entraînement de modèles d’IA pour la physique. Le poste couvre l’automatisation des simulations, l’intégration physique-ML et la collaboration avec des partenaires de l’automobile, de la Formule 1 et de l’aérospatiale.
Repères sur BeyondMath
- Domaine officiel
- beyondmath.com
- Offres ouvertes
- 6
Détails de l’offre
La description complète publiée par BeyondMath.
Description de l’offre
Simulation Engineer 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 simulationworkflows—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 andAerospace t 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. We receive a large number of applications and take the time to carefully review each one. While this means our response time might be a bit slower, we deeply appreciate your patience
Prérequis
- Postgraduate Degree (MSc/PhD) in Aerospace, Aeronautical, Mechanical Engineering, or Mathematics
- Extensive experience with industry-standard solvers and mesh generation
- Strong theoretical background in incompressible/compressible flow, turbulence modeling, and heat transfer
- Proven ability to take a project from a raw CAD file to a fully validated, post-processed simulation
- Ability to bridge classical engineering disciplines and modern machine learning teams
Avantages mentionnés
- Full Ownership
- High Impact
- Elite Team
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