Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy rapidly. Combining first-principles thinking with cutting-edge technology, we are building a radically better energy system. Having raised $210M from top-tier investors, we are creating a fully integrated energy company that develops solar, wind, and hydrogen projects, real-time power trading, and distributed energy installations. By selling directly to consumers, we lower costs and pass on savings while building the Energy Network — a decentralised platform of smart devices to electrify homes, shift usage to off-peak hours, and help balance the grid. This network supports grid stability, a critical foundation for scaling AI data centers and other energy-intensive industries.

As an Applied AI Engineer, you will join our cutting-edge AI team to develop AI-powered features that enhance both customer experience and internal operations. You will work on consumer-facing projects such as the Energy Co-Pilot and Speedy Onboarding process leveraging VLM/LLM tools, and collaborate across teams to build AI tools that improve productivity and streamline workflows. Your responsibilities will include designing, developing, and deploying AI-driven features, integrating AI models with backend systems, aligning AI solutions with real-time market conditions, and continuously improving models to optimise trading strategies based on weather and demand forecasts. Staying current with the latest applied AI and machine learning advancements, you will apply these innovations to solve real-world energy challenges and ensure AI tools perform efficiently and effectively.

Experience
Minimum 3 years of engineering experience.
Proven experience as a Backend Engineer with strong interest and practical experience in applied AI or machine learning.
Strong programming skills in Python or similar languages with familiarity in AI/ML libraries such as TensorFlow and PyTorch.
Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production.
Solid understanding of cloud technologies, containerisation, and building scalable AI applications.
Ability to integrate AI/ML models into real-world applications focusing on usability and performance.
Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment.
Experience working with large datasets, particularly related to demand and supply forecasting.

About you
You have a passion for applied AI and its potential to transform energy systems.
You thrive in collaborative environments, working closely with engineers, data scientists, and business teams.
You are proactive in staying up to date with AI and machine learning advancements and enjoy applying them to solve complex problems.
You have strong communication skills and a practical mindset to deliver impactful AI solutions.

Qualifications
Relevant degree or equivalent experience in computer science, engineering, or a related field is preferred but not mandatory.

Bonus
Experience or strong interest in energy markets and trading strategies.
Understanding of weather forecasting, energy demand patterns, and production modelling.
Exposure to Natural Language Processing (NLP) or related AI fields.