---
title: 'Machine Learning Engineer at BeyondMath'
canonical: 'https://feeny.ai/job/machine-learning-engineer-beyondmath-london-xqf3pz0em99x'
type: 'job'
last_seen: '2026-09-12'
---

# Machine Learning 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/3fe712b8-c4bc-4723-9fa7-a2a276d22c74

## Job description

Machine Learning 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.

## The Role

As a Machine Learning Engineer, you’ll play a central role in advancing our Generative Physics simulation platform. You’ll work at the intersection of ML research and engineering contributing to core model development, shaping model architecture, and delivering performant systems that integrate seamlessly into our real-world design optimization workflows. You'll work closely with our ML research team, software engineers, and industry partners to deploy robust, scalable models that deliver real-world impact.

## Responsibilities

- Physics-Focused AI Model Development: Design and train deep learning models for physics simulation across aerodynamic and engineering domains.
- Scalability & Performance: Drive optimization efforts for model inference speed, accuracy, and robustness on large-scale industrial datasets.
- Geometry Representation: Research effective ways to represent geometric design variations for efficient use by machine learning models.
- Production Integration: Partner with engineering teams to deploy and monitor models in production-grade pipelines and tools.
- Architecture & Design: Contribute to design decisions around model and data architecture, tooling, and ML infrastructure.

Essential Requirements

- Industrial Experience: Strong track record applying ML to complex real-world problems (ideally including geometry or physical systems).
- Foundational Knowledge: Deep understanding of machine learning theory, including optimization, generalisation, and various model architectures.●
- Programming: Strong python skills and experience with deep learning libraries (TensorFlow/PyTorch/JAX).
- Communication: Ability to clearly explain complex ML concepts and research findings to both technical and non-technical audiences.
- Education: Master's Degree (PhD preferred) in Machine Learning, Computer Science, or a related quantitative field.

Highly Desirable

- Aerodynamics/CFD Expertise: Familiarity with aerodynamic principles and computational fluid dynamics is a major plus.
- Design Optimization: Prior experience in optimization algorithms, particularly inthe context of engineering design.
- Physics/Science ML: Experience integrating physical laws or constraints intomachine learning models.

Why Join Us?

- Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry.
- High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport.
- Elite Team: Work alongside veterans from world-leading AI labs and engineering firms 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)

## Other roles at BeyondMath

- [AI Researcher](https://feeny.ai/job/ai-researcher-beyondmath-london-088es291n6wb) — London, United Kingdom
- [Technical Account Director](https://feeny.ai/job/technical-account-director-beyondmath-london-cbbny9s4913a) — London, United Kingdom
- [Simulation Engineer](https://feeny.ai/job/simulation-engineer-beyondmath-london-82fyq9tyjp4b) — London, United Kingdom
- [Software Engineer](https://feeny.ai/job/software-engineer-beyondmath-london-mwrjhxz5n451) — London, United Kingdom
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-yuno-europe-qk68kdrz5rgw) — Europe
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-pangram-labs-brooklyn-e3hhh2tc2855) — Brooklyn, NY
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-gatik-ai-santa-clara-qj4vvbdeqt4x) — Santa Clara, CA
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-wynd-labs-remote-whe42v314npy)
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-blissway-inc-denver-x6g0dsrp5q6v) — Denver, CO
- [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-blissway-inc-denver-gy2xqv8xdt4a) — Denver, CO