We’re looking for a Frontend Engineer to build interfaces that make complex distributed systems intuitive, legible, and visually striking. This is a hands-on IC role requiring the overlap of design and engineering skill. It does not require deep ML expertise or distributed system experience.

Day to day, you’ll work closely with one of our Founding Scientists, who guides the top-level design of the system and report directly to the CEO. Opinionated taste and high autonomy is critical—the design space is wide open. The system we’re constructing (large-scale multi-party ML training) demands novel paradigms. Thinking from first principles about how this should be presented along with the ability to then implement it, is core to the role.

Responsibilities

• Architect and implement high-quality frontend systems, primarily visualisations and interfaces for real-time ML training data.

• Distill incredibly complex, dense data streams into clear, compelling visuals

• Contribute occasionally to lighter design needs (presentations, illustrations, technical blog content)

Preferred

• Familiarity with observability/metrics ecosystems (Prometheus, Grafana)

• Portfolio demonstrating strong design + engineering ability.

• High-level understanding of modern ML (e.g., know what a “training loss” is)

Not Preferred

• Corporate/Standard Design and UX experience. For example - if you look at Google's material design v3 and think 'damn that's nice' - that would be bad.