At a Glance
- Tasks: Lead the development of AI-driven simulation software for advanced engineering.
- Company: PhysicsX, a deep-tech innovator with a focus on hardware and software integration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on innovation and collaboration.
- Why this job: Join a team pushing the boundaries of engineering with cutting-edge AI technology.
- Qualifications: Experience in machine learning infrastructure and high-performance computing.
The predicted salary is between 80000 - 100000 £ per year.
About Us
PhysicsX is a deep‑tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI‑driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high‑fidelity, multi‑physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations – empowering engineers to push the boundaries of possibility.
Our customers include leading innovators in Aerospace.
- Experience with geometric deep learning or neural operators, architectures that operate on meshes, point clouds, or graphs.
- Background in HPC for simulation engineering, familiarity with how CFD/FEA workflows generate and consume data.
- Experience building model serving infrastructure with latency and throughput requirements.
- Familiarity with experiment tracking tools.
Principal Machine Learning Infrastructure Engineer employer: Physicsx
At PhysicsX, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our team thrives in a flat structure where every voice is valued, and we offer meaningful benefits such as equity options, generous parental leave, and a commitment to personal development. Located in Shoreditch, our hybrid work model allows for a sustainable work-life balance while tackling impactful challenges in AI-driven engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Machine Learning Infrastructure Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at PhysicsX or similar companies. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got projects or contributions related to machine learning infrastructure, share them on platforms like GitHub. It’s a great way to demonstrate your expertise and passion.
✨Tip Number 3
Prepare for the interview by diving deep into the tech stack used at PhysicsX. Brush up on your knowledge of HPC, geometric deep learning, and AI-driven simulations. The more you know, the more confident you'll feel!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Principal Machine Learning Infrastructure Engineer
Some tips for your application 🫡
Show Your Passion for Deep-Tech:When writing your application, let your enthusiasm for deep-tech and AI-driven solutions shine through. We love seeing candidates who are genuinely excited about pushing the boundaries of engineering and manufacturing.
Tailor Your Experience:Make sure to highlight your relevant experience in HPC, geometric deep learning, or any specific projects that align with our work at PhysicsX. We want to see how your background can contribute to our mission!
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and fit for the role. Avoid jargon unless it's necessary!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Physicsx
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning infrastructure, especially in relation to high-performance computing (HPC) and simulation engineering. Be ready to discuss specific projects or experiences where you've worked with geometric deep learning or neural operators, as this will show your expertise and relevance to PhysicsX.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled complex problems in previous roles. Think about examples where you've optimised workflows or improved model serving infrastructure. Highlighting your ability to meet latency and throughput requirements will resonate well with the interviewers.
✨Familiarise Yourself with Their Tech Stack
Do some homework on the tools and technologies that PhysicsX uses, especially around AI-driven simulation software. If you have experience with experiment tracking tools like Weights & Biases, be sure to mention it. This shows that you're not just a fit for the role but also genuinely interested in their work.
✨Ask Insightful Questions
Prepare thoughtful questions that demonstrate your interest in the company and its projects. Inquire about their approach to multi-physics simulation or how they envision the future of AI in engineering. This not only shows your enthusiasm but also helps you gauge if the company aligns with your career goals.
