Quick overview
Job description
Fuse Energy is an energy startup on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system.
We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.
We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, using AI across the business, and installing distributed energy in homes. By selling directly to consumers we cut out the middleman, lower costs and pass the savings on to our customers.
As an AI Research Scientist, you will do the pre-training research behind the Energy Foundation Model: one model, trained on generation, the grid, demand, weather and price together, that learns the relationships between them that a human analyst would never think to write down. Today we model each forecasting problem separately; you will work out how a single model should be built and trained, and show that it works. We have data nobody else can buy, including household-level consumption from hundreds of thousands of UK homes, which outside trading firms cannot get. The work is research: experiments, evidence and papers that shape how we forecast, hedge and trade.
- Do the pre-training research for the Energy Foundation Model
- Design the architecture, inputs and training objectives for one model across generation, grid, demand, weather and price data
- Run pre-training experiments and find what actually improves results
- Build rigorous evaluations and honest backtests, with calibrated uncertainty
- Train on household-level data without leaking personal information
- Write up findings as research, and work with our quants and engineers who take the model into production
- Competitive salary and eligibility for equity
- Biannual bonus scheme
- Fully expensed tech to match your needs
- Private health insurance
- Breakfast and dinner allowance for office-based employees
As we hire globally, benefits vary by location.
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