You will lead the development of a unified platform that bridges the gap between traditional computational fluid dynamics (CFD) and modern machine learning. By building high-performance multiphysics solvers from scratch and training advanced neural operators, you will empower engineers to develop complex products faster and more sustainably through differentiable simulation.
This job is no longer actively hiring. Talk to Jack to find live roles.
Founding Engineer (Multiphysics & Physics AI) at Gradient Dynamics
Are you tired of the artificial wall between traditional CFD and modern ML? This London-based deep tech startup is hiring a Founding Engineer to build a unified Physics AI platform from the ground up. You'll work at the intersection of GPU-native solvers and neural operators to solve the world's most complex engineering challenges. If you have a PhD-level background in computational physics and high-performance scientific computing, this is your chance to shape the future of sustainable engineering design.
Want to apply for this role?
This role is no longer actively hiring, but Jack can still help you discover similar open roles that fit.
Location
London, United Kingdom
Compensation
Not Disclosed
Company
Gradient Dynamics
Role overview
Gradient Dynamics develops GPU-native simulation and optimization technology that helps engineering teams move faster from concept to production.
What you will do
- Develop and optimize GPU-native multiphysics solvers using finite volume or finite element methods to maximize throughput on HPC systems.
- Design, train, and benchmark neural operator architectures (like FNO or DeepONet) against existing numerical techniques for engineering applications.
- Architect systems at the intersection of computational geometry and parallel architectures to underpin how the platform handles complex engineering designs.
Who this is a fit for
- Holds a PhD or equivalent industry experience in computational physics, applied mathematics, or machine learning for scientific applications.
- Possesses a proven track record of writing production-quality scientific code and numerical methods from scratch, beyond just scripting in existing frameworks.
- Demonstrates deep expertise in GPU programming (CUDA, JAX, or XLA) and a strong grasp of governing equations like Navier-Stokes and energy equations.
Why this role is remarkable
- Rare opportunity to build a unified simulation-ML system from first principles, eliminating the traditional wall between CFD experts and AI researchers.
- Direct impact on a full-stack platform designed to solve the world’s hardest engineering problems across aerodynamics, thermal management, and multiphysics.
- Work at the bleeding edge of Scientific ML (SciML), utilizing JAX, CUDA, and neural operators to redefine how industrial designs are represented and tested.
How Jack & Jill work together
I get to know what you’re great at, then find roles you’d never find yourself.Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.
I recruit from Jack’s network and make the intro when I spot a great match.And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.
Jack gets to know what you're great at and what you want next, then searches 15 million jobs daily and helps you discover roles at companies like this.
Meet Jack
What happens next?
Jack’s an AI agent for job searching and career coaching. He works for you.
Jill is the AI recruiter working for the company. She recruits from Jack’s network.
If your profile’s a match and Gradient Dynamics wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.