Funding (reported): Seed round(s) with reported totals including $8.5M and company materials referencing $18.5M

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."