Hybrid Applied AI Engineer

at Fuse Energy

• Job title: Applied AI Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Cloud, Python, PyTorch, Tensorflow
• Location requirements: Hybrid, London, United Kingdom

About the role

• Applied AI Engineer creating AI-powered features and tools to enhance the energy experience at Fuse Energy. Involved in consumer-focused projects and internal collaboration to boost productivity.

Responsibilities

• Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)
• Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows
• Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms
• Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing
• Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts
• Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space
• Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively

Requirements

• Minimum 3 years of engineering experience
• Proven experience as a Backend Engineer with a 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 (TensorFlow, PyTorch, etc.)
• 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 in relation to demand and supply forecasting
• **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 other related fields

Benefits

• Competitive salary and an equity sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Paid annual leave
• Breakfast and dinner allowance for office based employees