At a Glance
- Tasks: Lead the development of a groundbreaking GPU-native Physics AI platform for engineering simulation.
- Company: Exciting London-based deep tech startup at the forefront of engineering innovation.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Join a dynamic team tackling the world's toughest engineering challenges with cutting-edge technology.
- Why this job: Make a real impact by bridging traditional CFD and modern machine learning in engineering.
- Qualifications: PhD or equivalent experience in computational physics, applied mathematics, or machine learning.
The predicted salary is between 60000 - 80000 £ per year.
London-based deep tech startup building a GPU-native Physics AI platform for engineering simulation and design optimization.
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.
Location: London, UK
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.
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.
The ideal candidate:
- 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.
Founding Engineer (Multiphysics & Physics AI) at GPU-native engineering simulation startup employer: Jack & Jill
As a pioneering deep tech startup based in London, we offer an exceptional work environment that fosters innovation and collaboration. Our culture is built on the principles of creativity and scientific exploration, providing employees with unique opportunities for professional growth while working on cutting-edge technology that addresses some of the most challenging engineering problems. Join us to be part of a dynamic team where your contributions will have a direct impact on the future of engineering simulation and design optimization.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Engineer (Multiphysics & Physics AI) at GPU-native engineering simulation startup
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to multiphysics or AI. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of GPU programming and numerical methods. Practice coding challenges and be ready to discuss your past projects in detail—this is your chance to shine!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight how your experience aligns with our mission to revolutionise engineering simulation.
We think you need these skills to ace Founding Engineer (Multiphysics & Physics AI) at GPU-native engineering simulation startup
Some tips for your application 🫡
Show Your Passion for Physics AI:When writing your application, let your enthusiasm for multiphysics and Physics AI shine through. We want to see how your background aligns with our mission to bridge traditional CFD and modern machine learning.
Highlight Your Technical Skills:Make sure to showcase your expertise in GPU programming and numerical methods. We’re looking for someone who can write production-quality scientific code, so don’t hold back on detailing your experience with CUDA, JAX, or any relevant frameworks.
Tailor Your Application:Customise your CV and cover letter to reflect the specific requirements of the Founding Engineer role. We appreciate candidates who take the time to connect their skills and experiences directly to what we’re building at StudySmarter.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity to shape the future of engineering simulation.
How to prepare for a job interview at Jack & Jill
✨Know Your Physics and Maths
Brush up on your knowledge of computational physics and applied mathematics. Be ready to discuss key concepts like the Navier-Stokes equations and how they relate to multiphysics simulations. This will show that you’re not just familiar with the theory but can also apply it practically.
✨Showcase Your Coding Skills
Prepare to demonstrate your coding abilities, especially in GPU programming with CUDA or JAX. Bring examples of your past work where you've written production-quality scientific code. If possible, have a small project or code snippet ready to discuss during the interview.
✨Understand the Company’s Vision
Research the startup's mission and the specific challenges they aim to solve with their Physics AI platform. Being able to articulate how your skills align with their goals will set you apart and show your genuine interest in the role.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of finite volume or finite element methods. Practice explaining complex concepts clearly and concisely, as this will demonstrate your ability to communicate effectively with both CFD experts and AI researchers.
