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- Tasks: Design and train AI models for physics simulation in engineering.
- Company: BeyondMath, a pioneering startup transforming engineering with AI.
- Benefits: Competitive salary, flexible work hours, and opportunities for growth.
- Other info: Collaborative environment with top-tier VCs backing our innovative vision.
- Why this job: Join a mission-driven team solving real-world engineering challenges with cutting-edge technology.
- Qualifications: Experience in machine learning and a passion for physics.
The predicted salary is between 36000 - 60000 £ per year.
About BeyondMath
BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world’s hardest physical engineering challenges in automotive, aerospace, and energy.
The Role
As a Machine Learning Engineer, you’ll play a central role in advancing our Generative Physics simulation platform. You’ll work at the intersection of ML research and engineering—contributing to core model development, shaping model architecture, and delivering performant systems that integrate seamlessly into our real-world design optimization workflows. You'll work closely with our ML research team, software engineers, and industry partners to deploy robust, scalable models that deliver real-world impact.
Responsibilities
- Physics-Focused AI Model Development: Design and train deep learning models for physics simulation across aerodynamic and engineering domains.
- Scalability
Machine Learning Engineer employer: BeyondMath
Contact Detail:
BeyondMath Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We can’t stress enough how personal connections can open doors that applications alone can’t.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and physics simulations. We love seeing practical examples of your work, so make sure to highlight your best stuff!
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. We recommend practicing common interview questions and even doing mock interviews with friends or mentors to build confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who want to make an impact in the world of AI.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Your Passion for Physics and AI: When writing your application, let your enthusiasm for physics and AI shine through. We want to see how your background and interests align with our mission to reshape engineering using AI. Share any relevant projects or experiences that highlight your passion!
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Machine Learning Engineer role. Highlight your experience in deep learning and physics simulation, and don’t forget to mention any specific tools or technologies you’ve worked with that are relevant to the job.
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured documents that make it easy for us to see your qualifications. Use bullet points where appropriate and avoid jargon unless it’s necessary to showcase your expertise.
Apply Through Our Website: We encourage you to apply directly 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 us you’re serious about joining our team at BeyondMath!
How to prepare for a job interview at BeyondMath
✨Know Your Physics
Make sure you brush up on your physics knowledge, especially in areas relevant to the role. Be prepared to discuss how you can apply machine learning techniques to solve complex physical problems, as this will show your understanding of the intersection between ML and engineering.
✨Showcase Your Projects
Bring examples of your previous work that demonstrate your experience with deep learning models and physics simulations. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will help the interviewers see your practical skills in action.
✨Understand the Company’s Mission
Familiarise yourself with BeyondMath's mission and the specific challenges they are tackling in the engineering space. This will not only help you tailor your answers but also show your genuine interest in contributing to their goals.
✨Prepare for Technical Questions
Expect technical questions related to machine learning algorithms, model architecture, and performance optimisation. Brush up on key concepts and be ready to discuss how you would approach specific problems they might face in developing scalable AI models for physics simulation.