---
title: 'Simulation Engineer at BeyondMath'
canonical: 'https://feeny.ai/job/simulation-engineer-beyondmath-london-82fyq9tyjp4b'
type: 'job'
last_seen: '2026-09-12'
---

# Simulation Engineer at BeyondMath

- **Company:** BeyondMath
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-03-13
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/beyondmath/63725706-95b3-476c-944e-a85873fe584a

## Job description

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

## About BeyondMath

## Company Overview
- **One-liner**: BeyondMath develops a foundational AI model of physics that enables engineers to run full-fidelity simulations up to 1,000× faster than traditional solvers, compressing design cycles from months to minutes.
- **Entity Type**: Private (Seed-stage)
- **Headquarters**: London, United Kingdom (also has presence in Cambridge, UK and the United States)
- **Founded**: 2022
- **Founders**: Alan Patterson (Co‑Founder & CEO), Darren Garvey (Co‑Founder)

## Core Business
- **Primary industry/industries**: Simulation software, Artificial Intelligence, Engineering design (aerospace, automotive, energy, defense, semiconductors, construction, telecommunications, electronics)
- **Target customers**: B2B – engineering teams in aerospace, automotive, energy, defense, and other hardware-intensive industries
- **Mission or purpose statement**: “By going beyond the limits of traditional data, computation, and simulation, our platform not only brings design to a new scale and speed, but also enables breakthroughs that might otherwise remain undiscovered.” – [beyondmath.com](https://beyondmath.com/about)

## Products & Services
- **Generative Physics Engine (Platform)**: A cloud-based SaaS platform that accepts raw geometry (no solver‑ready mesh required) and runs transient simulations of pressure, velocity, temperature, and other physical fields in real time. The engine is powered by the world’s first foundational AI model trained on the fundamental laws of physics, enabling engineering‑grade accuracy and 1,000× speed improvements over conventional CFD/FEA solvers. The platform also provides visualisation, export, and integration APIs for existing workflows. – [beyondmath.com](https://beyondmath.com)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total Funding – **$20.3M** (USD) across three rounds; latest **$18.5M Seed Round** closed in February 2026
- **Notable Investors/Partners**: Cambridge Innovation Capital (lead, 2026 round), UP Partners (lead, 2024 & 2022 rounds), and other undisclosed investors. – [cbinsights.com](https://www.cbinsights.com/company/beyondmath)
- **Growth Signals**: Headcount grew **22.2% YoY** (19 employees as of mid‑2026); placed 3rd in the **Siemens Industrial AI Awards**; exhibited at **NVIDIA GTC Paris**. – [uk.linkedin.com](https://uk.linkedin.com/company/beyondmath)

## Competitive Advantages
- **Foundational physics AI**: Unlike traditional surrogate models trained on limited legacy data, BeyondMath’s model understands the underlying laws of physics, making it generalizable across geometries, industries, and boundary conditions.
- **No pre‑processing required**: Users upload raw geometry directly – no solver‑ready mesh or manual preprocessing, dramatically reducing setup time.
- **Speed & scalability**: 1,000× faster simulation enables engineers to explore thousands of design variants in the time it would take to run a single traditional simulation.
- **Team depth**: The founding team includes veterans from Google, eBay, Amazon (Evi Technologies), and Palantir, with deep expertise in machine learning, software engineering, and commercial scaling.

## Strategic Focus
- **Scale the foundational model**: Expand the AI’s training data and capabilities to cover more physics domains (e.g., electromagnetics, aeroacoustics, multiphysics) and more industries.
- **Enterprise adoption**: Build out the commercial team (recently hired a Technical Account Director) and secure multi‑year contracts with large engineering organizations.
- **Ecosystem integration**: Offer APIs and plugins to integrate directly into customers’ existing CAD/PLM workflows.

## Why Work Here
- **Cutting‑edge AI & physics**: Engineers and researchers get to work on the frontier of AI and computational physics, solving real‑world problems in aerospace, energy, and defence.
- **Small, high‑impact team**: With only ~20 people, every hire has outsized influence on both the product and the company direction.
- **Research‑friendly culture**: The team includes leading AI researchers from top institutions (Imperial College London, University of Oxford) and the company encourages publishing and participation in industry awards.
- **Hybrid/remote flexibility**: Although headquartered in London, the team spans the UK and US, and job postings do not mandate full‑time in‑office presence – likely a flexible work arrangement.
- **Notable perks**: Early‑stage equity, direct mentorship from founders with deep tech (Google, Palantir) experience, and the chance to shape the product roadmap from day one.

## Sources
1. [beyondmath.com (product & mission)](https://beyondmath.com)
2. [beyondmath.com (about team & story)](https://beyondmath.com/about)
3. [uk.linkedin.com (company details & headcount)](https://uk.linkedin.com/company/beyondmath)
4. [cbinsights.com (funding & investors)](https://www.cbinsights.com/company/beyondmath)
5. [jobs.ashbyhq.com (open positions)](https://jobs.ashbyhq.com/beyondmath)

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