Physics Modelling Lead
4 weeks ago
Luffy AI is a pioneering high-tech company specializing in the development of adaptive neural networks for industrial control. Our innovative technology enables the creation of digital twins that can be trained in simulation and successfully transferred into real-world systems. This allows us to overcome the challenges of using Machine Learning in control system applications.
Our cutting-edge AI technology empowers manufacturers to improve productivity and reduce energy consumption. It also enables robotics companies to extend the operating envelope of their machines, making them more robust and capable. This revolutionary control technology is a key enabler of Industry 4.0, with vast potential in foundation industries such as metals, glass, and cement manufacturing, as well as robotic systems like industrial arms, drones, and sub-sea UAVs.
The RoleWe are seeking a highly skilled and experienced Senior Simulation & Modelling Engineer to join our multidisciplinary delivery team. The team is responsible for building our suite of AI and physics model products for control and optimization of industrial equipment. We are looking for someone with deep practical experience in physical modelling who is eager to help us solve real-world problems with artificial intelligence.
Our customers span a range of robotics and industrial process companies. When training AI networks for these applications, we require digital twin models that expose the networks to a representative approximation of the system dynamics and phenomena encountered. AI controllers are trained on these digital twins using Reinforcement Learning techniques, and in some instances, the physics model is also a product offering. These digital twin models are built on in-house physics engines, which are configured for the application under development. In this role, you will be both expanding our existing physics engines and developing new frameworks for future markets. Working closely with AI application engineers, you will design physics APIs to support the development of AI training environments.
Key Responsibilities- Implement mathematical models of real-world physical systems. Develop our core physics engines and reference models (e.g. aerodynamic, mechanical, industrial processes), with a focus on computational performance.
- Assist the AI team with digital twin development. Ensure that game engines are fit for their intended uses (numerical stability, performance, accuracy).
- Work with application engineers to capture relevant physics underpinning a customer's application, developing requirements for the physics engines.
- Maintain good code quality standards across our physics code bases.
- Develop visualization tools for digital twins and physics engines, alongside other developers.
- Investigate problem areas to advance knowledge, evaluate new approximations and numerical techniques for validity and performance.
- University degree in a relevant area of engineering/science (physics, maths, computer science) or an equivalent qualification. An advanced degree may be an advantage but is not required.
- 5+ years of relevant experience in one of games physics programming, digital twin development, chemical process modelling, or other physical simulations balancing performance and fidelity.
- Skilled in software architecture with a good understanding of algorithm design, algorithmic complexity, managing computational resources, design patterns, and API design.
- Strong understanding of the numerical techniques related to physics codes, e.g. differential equation solvers, numerical integration schemes, statistical sampling, finite element methods
- Strong mathematical skills, including vector calculus, linear algebra, 3D geometry.
- Strong programming skills in Python, experience with C++ desirable.
- Ability to produce visualization tools that support simulation models (graphing and 3D visualizations, Python/JS).
- Must be able to autonomously research and learn about new systems/processes. Be able to make and justify approximations relevant to the simulation fidelity required.
- Good understanding of code profiling, performance, and numerical optimization techniques.
- Familiarity with testing frameworks and continuous integration.
- A desire to help other people solve their problems.
- Excellent communication skills.
- Passionate about writing robust, efficient code that is well thought out and tested.
- Fast learner, comfortable picking up new technologies and techniques.
- Product-focused, good prioritization skills.
- T-shaped person, deep expertise in a few areas but able to be a generalist when needed.
- Team player.
- Enjoys teaching junior staff about how to improve their modelling and code.
- Strong organizational skills.
- Full-time salary of £50k - £70k, depending on experience and capability assessment during the interview process.
- EMI share options scheme.
- 25 days annual leave, plus bank holidays.
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