About the role
About Us At Axle Energy, we’re building the infrastructure that will underpin the decarbonised energy system. Our software moves energy usage to times when electricity is cheap and green, by controlling vehicle charging, heating systems, and home batteries. We control hundreds of thousands of energy assets. We’re building in a legacy industry and moving gigawatt-hours of electrons in the real world, but we operate at lightning speed, and we’re growing
the team to meet customer demand. We’re proud to be supported by world-leading investors, including Accel. Read more about what we’re building here .
About
the role We're hiring full stack data scientists who love to get into the nitty gritty of the domain, have an instinct for commercial value, and own the entire process from data exploration to production. 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 wear many hats) Familiarity with time-series data Tech stack 🐍 We build in Python + React for the frontend (less relevant for this role) 🐋 Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility. 🤖 Unlimited Claude Code tokens - we are aggressive users and explorers of AI, and encourage everybody to reconsider their workflows regularly ☁️ 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