Member technical staff; Frontend Engineer

Member of the technical staff (Frontend Engineer)

Engineering Zürich Office Full-time

Physical AI, a real model of the world, is the next trillion dollar opportunity and a foundational pillar for energy, robotics and superintelligence.

At Jua we are building it now. Our models already run on four continents and help power the energy buildout needed to support ever larger intelligence.

We are assembling a world‑class team of researchers and entrepreneurial minds to turn this model into reality at global scale. If you want the opportunity of your life, come build physical AI with us.

We’re hiring a front‑end–leaning full‑stack engineer to help define and build the future of our platform.

You should have a strong sense of design, deep empathy for users, and a general grasp of machine learning or the latest AI technologies. You don’t need to be a researcher or a math prodigy for this role, but we are specifically looking for candidates who approach problems from first principles and thrive in a culture that grants significant individual responsibility.

We value people who are deeply curious about how systems fundamentally work—whether it’s computers, satellites, AI, societies, or human psychology—and who are eager to collaborate with other exceptional individuals to broaden their perspective even further.

You’ll thrive here if you’re driven to push the boundaries of the current state‑of‑the‑art and expand human knowledge in forecasting and simulating the future. If you believe that hard work leads to outsized returns, enjoy taking ownership and building exceptional products, and have a talent for transforming complex systems into clear, fast, and elegant experiences, this is the place for you.

Jua is currently evolving its core platform into two focused products:

• A developer‑focused API platform designed for integrators and quants to access our prediction models & data products for their daily trading operations. These users care about simple, smart and clean interfaces, low‑latency data, and seamless integration via our SDK.
• An AI‑native product built for decision‑makers like traders and meteorologists who want answers, not just data. Think of a geospatial reasoning layer for planet earth. This product uses agents based on language models to interact with our simulation models to deliver insights and decision support.

You’ll simplify complexity for non‑technical users while enabling technical users to work with precision and control.

Location: Although we are a global team, it is a requirement that applicants are currently based in Zurich, Switzerland
, working on a Hybrid working model.

• Frontend
  :
  Type Script, React & Tailwind
• Design
  :
  Ultra minimalistic, lightweight design system. For some time now, we've entirely skipped the classic Wireframe–Figma–Component workflow and just vibe code most frontend components directly.
• Visualization
  : ECharts, Three.js, Mapbox, Plotly, Deck.gl for map-heavy and time‑series UI
• Backend
  :
  Python, FastAPI, Web Sockets, gRPC endpoints, little bit of rust, Zarr & Clickhouse SQL db
• ML Interfaces
  :
  Real‑time inference, model metadata, probabilistic forecasts, & geospatial datasets

• Own and shape full features and products end‑to‑end to support multiple products, user personas, and evolving data needs by building reusable UI components
• Build intuitive, high‑performance UIs for both technical users and decision‑makers with a focus on clarity and responsiveness
• Develop rich interfaces for time‑series, geospatial, and probabilistic data, turning raw model outputs into decision‑support tools
• Collaborate with researchers and engineers to make complex model outputs usable and understandable

• 4+ years of front‑end engineering with React and Type Script
• Strong aesthetic sensibility and user‑centered design mindset
• Proven ability to ship fast, accessible, maintainable UIs at a high‑quality bar
• A desire to understand domain‑specific workflows in energy, weather, or trading, and use that knowledge to build better interfaces
• Exposure to data or ML APIs and eagerness to integrate model outputs into production UIs
• Familiarity…