About the job
Polaron, a pioneering spin-out from Imperial College London, was founded by Dr. Isaac Squires, Dr. Steve Kench, and Dr. Sam Cooper. Our mission is to leverage engineering, artificial intelligence, and materials science to create the next generation of materials that will shape the future.
We aspire to lead at the intersection of AI and materials science, merging scientific rigor with practical engineering to foster sustainable, high-performance materials. Our work addresses not just intellectual challenges but the immediate and significant impact of advancing material technologies. From powering electric vehicles with cutting-edge batteries to optimizing alloys for turbines and reducing aircraft weight with innovative composites, our contributions are vital to contemporary life.
By accelerating the development, design, and manufacture of these materials, we enhance the global capacity to cultivate a sustainable future.
We are in the process of developing a cloud-based SaaS platform that enables materials engineers to seamlessly utilize advanced image-based AI, facilitating insightful analysis and rapid innovation with ease.
Key Highlights:
- A dynamic team of 12, rapidly expanding.
- Located in East London (Shoreditch Exchange, Hoxton).
- Supported by groundbreaking research and robust industry partnerships.
What We Are Creating:
At Polaron, we are crafting state-of-the-art tools that empower materials scientists and manufacturers to utilize advanced AI vision models directly from their web browsers.
Our application features:
- A data-intensive visual interface for exploring, interacting with, and analyzing complex datasets (including high-resolution image data) in a browser optimized for performance and scalability.
- Interactive visualization and analysis tools that integrate 2D, 3D, and graphical data representation.
- A computational orchestration layer that seamlessly connects user experiences with machine learning models, enabling sophisticated analyses and simulations.
- Scalable AI infrastructure for training, serving, and executing complex machine learning workflows across distributed environments.
Why We Are Hiring:
We are entering a phase of rapid product adoption and platform scaling, with our technology being deployed in real-world research settings.

