Frontend SWE

Want to build the interface layer for an AI scientist?

You’ll join a team building autonomous AI agents designed to accelerate scientific discovery. The goal is simple, science moves too slowly, and they’re building systems that can change that.

This isn’t a typical frontend role. The product is an integrated research environment where scientists interact directly with AI models, workflows, and generated insights. Your work defines how usable that system actually is.

You’ll sit within the Platform team, working closely with researchers and product to turn complex, often messy scientific workflows into clear, intuitive interfaces.

The challenge is translating depth into clarity without losing fidelity.

You’ll be building high-performance frontend systems where data density, responsiveness, and usability all matter. Real-time interactions, dynamic visualisations, and scalable UI patterns are core to the product.

Your focus will include:

• Building performant React applications for data-heavy workflows
• Designing interfaces for real-time AI interactions and streaming data
• Creating modular, scalable design systems used across the platform
• Translating scientific and model outputs into usable visual interfaces

You’ll need strong frontend fundamentals, but more importantly, the ability to think in systems. Understanding how users navigate complexity, how interfaces guide decision-making, and how performance impacts usability at scale.

There’s a strong emphasis on performance engineering. You’ll be profiling rendering behaviour, optimising asset loading, and ensuring smooth interaction across browsers and devices.

The product itself sits at the intersection of AI, biology, and research tooling. If you’ve worked on complex internal tools, data platforms, or visualisation-heavy applications, this will feel familiar, just at a deeper technical level.

You’ll likely have experience building production frontend systems with React (or similar), working with TypeScript, and handling real-time data flows such as WebSockets or GraphQL subscriptions. Experience with visualisation libraries like D3, Deck.gl or Three.js is highly relevant here.

The environment is highly collaborative. You’ll work closely with researchers to anticipate how the product should evolve, not just respond to specs.

This is an onsite role based in San Francisco, working with a team focused on building something that genuinely pushes forward how science gets done.

Salary: $175,000 – $240,000 + equity
Location: San Francisco, onsite

If you’re interested in shaping how scientists interact with AI systems, apply today.