Applied AI Engineer

Fuse Energy; London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Fuse Energy is seeking an Applied AI Engineer to enhance customer experiences and internal operations through AI. This role focuses on developing AI features, optimizing internal tools, and ensuring alignment with market conditions while collaborating across teams to innovate within the energy sector. Ideal candidates will have a strong backend engineering background and a deep interest in applied AI.

Benefits

Competitive salary and stock options

Biannual bonus scheme

Fully expensed tech

Paid annual leave

Breakfast and dinner provided for office employees

Qualifications

• Minimum 4 years of engineering experience.
• Proven experience as a Backend Engineer with interest in applied AI.
• Experience with large datasets related to energy forecasting.

Responsibilities

• Design, develop, and deploy AI-powered features.
• Collaborate to integrate AI-driven features into platforms.
• Continuously improve AI models for user experience.

Skills

Python

Problem Solving

Applied AI

Machine Learning

Cloud Technologies

Large-scale Models

Tools

TensorFlow

PyTorch

Job description

At Fuse Energy, we are transforming the energy sector with innovative solutions that empower consumers. As we continue to scale, we are building a cutting-edge AI team that will play a critical role in developing intelligent, consumer-facing features, as well as internal tools that will drive productivity and innovation across the company.

Role Overview:
We are looking for an Applied AI Engineer to join our growing team at Fuse Energy. This position is ideal for an engineer who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. As an Applied AI Engineer, you will work on a variety of exciting projects, including consumer-focused features like the Energy Co-pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse Energy.

Requirements

• 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.
• Continuously improve and optimise AI models (including LLM and VLM) to provide a better user experience.
• Develop scalable, maintainable AI infrastructure to support a growing set of consumer-facing and internal AI features.
• Collaborate with the trading and operations teams to ensure the 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.

Skills & Qualifications:

• Minimum 4 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 (LLM/VLM) and deploying AI-driven solutions into production.
• Solid understanding of cloud technologies, containerization, 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.
• Familiarity with cloud-based platforms (AWS is a plus) and services related to AI/ML is a plus.
• Experience or strong interest in energy markets and trading strategies.
• Understanding of weather forecasting, energy demand patterns, and production modelling.
• Experience working with large datasets, particularly in relation to demand and supply forecasting.

Bonus:

• Experience in the energy or utilities industry.
• Exposure to Natural Language Processing (NLP) or other related fields.
• Familiarity with data engineering practices and working with large datasets.

Benefits

• Competitive salary and a stock options sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs!
• Paid annual leave
• Breakfast and dinner for office based employees