Lead Applied AI Researcher, Fuse Energy
Plus eligibility for equity and bonus scheme
Renewable energy supplier
Be an early applicant
Renewable energy supplier
201-500 employees
Be an early applicant
Plus eligibility for equity and bonus scheme
201-500 employees
Company mission
To make cheap renewable energy accessible for everyone.
Role
Who you are
- Strong experience applying modern AI models to real-world tasks with a track record of improving measured outcomes through experimentation
- Deep understanding of evaluations, dataset quality and failure analysis. You know how to distinguish a genuine improvement from an unreliable benchmark result
- Hands-on experience with several of model selection and routing, fine-tuning, reinforcement learning, agent systems or computer use
- Strong software engineering skills, including Python and the ability to build reliable experimental and production tooling
- Good judgment about cost, latency, reliability and risk, especially when deciding where deterministic checks or human review are needed
- Ability to move between research and implementation: formulate a hypothesis, run a rigorous test, inspect failures and ship what works
- Experience at a frontier AI lab or a team operating at a similar level of experimentation would be especially valuable
What the job involves
- Energy is a rare place to apply AI across the full stack: from helping customers and building software to operating physical infrastructure and trading power. Our ambition is to make energy cheaper and more abundant with AI, while building the energy and compute infrastructure that the next generation of AI will need
- Design experiments to find the best model and approach for each workload, balancing accuracy, latency and cost
- Own our evaluation framework: build high-quality datasets and golden answers, combine human and LLM judgments and measure how much confidence to place in each evaluator
- Explore post-training methods, including supervised fine-tuning and reinforcement learning
- Build agent harnesses that make long-running tasks reliable: tool use, deterministic checks, state tracking, retries, resource allocation and appropriate human approvals
- Set evaluation and escalation thresholds according to the consequences of failure
- Work with teams across Fuse to turn research results into production systems and bring new methods and hard-won lessons from the frontier of applied AI into the company
Salary benchmarks
Our take
Traditional energy companies often prioritise profit over sustainability, leading to high prices and reliance on fossil fuels. Fuse Energy aims to disrupt the energy market by offering lower prices and cleaner energy options.
It does this by building solar farms that ensure access to cheap, renewable energy. Its data science team forecasts energy demand and buys additional power from gas and electricity markets, providing a mix of renewable and traditional sources.
With €76M in annualised revenue and 7x year-on-year growth, it now supplies 50,000 homes and plans to expand into Ireland, Europe, and the US. Backed by new AI features and with investments into clean energy, Fuse is truly shaping up to redefine the future of home energy.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Jun 2026
$30m
SERIES B
Dec 2025
$70m
LATE VC
Total funding: $152m
Company HQ
Westminster, London, UK
Leadership
Alan Chang
(Co-Founder & CEO)Previously worked at Revolut for over 7 years in various roles, including SVP of Revenue and Operations, and CRO.
Charles O.
(Co-Founder & COO)Previously an Investor at Mosaic. They also worked at Revolut in Special Projects.
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