What You’ll Do
Take ownership of core architecture and development for a SaaS platform that enables materials engineers to interact with AI models directly in the browser. You’ll build rich, data-driven interfaces that handle high-resolution imaging and complex datasets, creating seamless experiences for visualising and analysing scientific data in 2D, 3D, and graph formats.
Design and implement the computational layer that connects frontend interactions with machine learning pipelines, ensuring efficient execution of AI workflows. You’ll develop infrastructure for training, serving, and orchestrating models at scale, using modern cloud technologies to support performance and reliability.
Within the first month, you’ll deliver tangible improvements to the platform. By month three, you’ll lead the end-to-end delivery of a customer-facing feature. By month six, you’ll be independently refining complex systems, influencing technical direction, and mentoring other engineers through code reviews and collaboration.
What We’re Looking For
- Strong background in full-stack development with a focus on scalable, high-performance web applications
- Hands-on experience with TypeScript, React, Next.js, Express, Prisma, Python, PyTorch, PostgreSQL, Docker, Kubernetes, AWS, and Terraform
- Proven ability to work autonomously in a high-ownership environment, shaping both code and product direction
- Experience integrating frontend applications with machine learning models, especially in scientific or data-intensive domains
- Ability to collaborate effectively with scientists, ML engineers, and product teams to translate complex concepts into functional software
Preferred Experience
- Work with AI/ML infrastructure or scientific computing systems
- Familiarity with computer vision or image-based models
- Background in materials science or related technical field
- Startup experience, particularly in early-stage or fast-growing environments
- Development for cloud-native SaaS platforms
Our Environment
We combine scientific precision with practical engineering to advance sustainable materials development. The culture values transparency, rapid iteration, and cross-functional collaboration. You’ll have meaningful influence over technical decisions and work closely with teams applying AI to real-world scientific challenges.
This role supports remote work during parts of the hiring process, with a hybrid setup centered in East London. The platform operates in a fast-moving environment where your contributions directly impact research and industry applications.
