BeyondMath

The Frontier of Generative Physics

BeyondMath is pioneering a fundamentally new approach to engineering simulation by training foundational AI models directly on the first principles of physics. Founded in 2022 by Alan Patterson and Darren Garvey, the London-based deeptech company has raised over $28 million to replace traditional, computationally heavy solvers with real-time AI. By delivering results up to 1,000 times faster, BeyondMath enables engineers in aerospace, automotive, energy, and motorsport to go from concept to validated design in days rather than months.

A Culture of First-Principles Thinking

At BeyondMath, the culture is driven by the ambition to solve hard, physical-world problems rather than just optimizing digital workflows. The team operates at the intersection of advanced machine learning and complex physics, requiring a deep appreciation for scientific truth. Engineers and researchers collaborate closely to ensure their AI models don't just estimate, but provide predictive accuracy that stands up to rigorous real-world testing.

What You'll Actually Do

Depending on your role, you'll be tackling some of the most complex challenges in deep learning and simulation. AI Researchers focus on scaling foundational physics models and pushing them from the lab into production environments. Software Engineers build the core infrastructure that powers the generative physics platform, ensuring it runs at industrial scale. Simulation Engineers work closely with customers to translate complex physical systems into the platform, validating results against traditional methods and real-world data.

Compensation & Benefits

While specific compensation data is limited, early indicators suggest competitive salaries for the London market. Machine Learning Engineers and AI Researchers can expect base salaries ranging from £58K to £108K, while Simulation Engineers typically see ranges between £40K and £70K. As an early-stage, well-funded startup, equity is likely a significant component of the total compensation package, offering substantial upside for early employees.

The Interview Process

Given the highly specialized nature of the work, the interview process at BeyondMath is rigorous and technically demanding. Candidates can expect an initial screening call with a recruiter, followed by deep-dive technical rounds assessing machine learning fundamentals, software engineering capabilities, or physics domain knowledge, depending on the role. Practical problem-solving and an understanding of how to apply AI to physical world challenges are key focus areas.

Why Join / Why Not

Why Join: If you're passionate about applying AI to solve tangible, real-world engineering problems, BeyondMath offers a unique opportunity to be at the forefront of generative physics. The recent $18.5M Seed round provides strong financial backing to scale their ambitious vision.

Why Not: The company is still in its early stages, meaning the environment is fast-paced and occasionally ambiguous. If you prefer the stability of established processes or are looking for a purely software-focused product without the complexities of physical world validation, this might not be the right fit.