About the role
About Us We’re hiring data scientists who get into the weeds, ship delightful software, and want to step into the arena in the fight against climate change. We’re building the software infrastructure for the decarbonised energy system, backed by some of the best investors in the world ( TechCrunch ). We make the technology to move energy usage to times when electricity is cheap and green. Our software controls vehicle charging, heating systems, and home batteries. We use machine learning to figure out what energy people will need, and when they'll need it. We control tens of thousands of energy assets, and we’re growing quickly. Read more about what we’re building here . What you will be doing: Building, optimising, and deploying models that operate reliably at scale Developing a deep understanding of energy markets, grid dynamics, and trading strategies Taking ownership of the full lifecycle of your work, from research and prototyping through to production Writing clean, production-quality code and contributing to robust, scalable systems Working beyond notebooks, turning ideas into real-world, productionised solutions It’d be nice if you could bring: Knowledge of the electricity system, specifically power trading Comfort speaking to clients (we’re a small team and we all wear many hats) Familiarity with time-series data Tech stack 🐍 We do everything in Python, because it allows data scientists and engineers to collaborate closely and move quickly. Our data scientists write lots of production code. We ❤️ Streamlit. 🎨 We try a bunch of things in Figma before we build them in code, because it's a fast and cheap way to get feedback. 🐋 Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility. ☁️ We deploy on GCP What's in it for you A meaningful slice of equity in Axle, alongside a competitive salary. We operate with a deliberately flat structure. We aim to keep pay equitable across the company, with a 1:1 median ratio between founder and team