Applied AI Engineer

Applied AI Engineer

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join us to design and develop AI features that enhance consumer energy experiences.
  • Company: Fuse Energy is revolutionising the energy sector with innovative, consumer-focused solutions.
  • Benefits: Enjoy competitive salary, stock options, 30 days paid leave, and fully expensed tech!
  • Why this job: Be part of a cutting-edge AI team making a real impact in the energy industry.
  • Qualifications: Experience as a Backend Engineer with a passion for applied AI and machine learning required.
  • Other info: Bonus points for familiarity with energy markets and large datasets!

The predicted salary is between 36000 - 60000 £ per year.

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.

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.

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.
  • 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:

  • 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!
  • 30 days paid annual leave per year (including bank holidays).
  • Deliveroo breakfast and dinner for office-based employees.

Applied AI Engineer employer: Fuse Energy

At Fuse Energy, we pride ourselves on being an innovative employer that is reshaping the energy sector through cutting-edge AI solutions. Our collaborative work culture fosters creativity and growth, offering employees ample opportunities to develop their skills while working on impactful projects that enhance consumer experiences. With competitive salaries, generous leave policies, and unique perks like fully expensed tech and Deliveroo meals, Fuse Energy is committed to supporting our team members both professionally and personally.
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Contact Detail:

Fuse Energy Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Applied AI Engineer

✨Tip Number 1

Familiarise yourself with the latest advancements in applied AI and machine learning, especially in the context of energy solutions. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.

✨Tip Number 2

Showcase your experience with large-scale models and AI-driven solutions by discussing relevant projects you've worked on. Be prepared to explain how you integrated AI/ML models into real-world applications, particularly in the energy sector.

✨Tip Number 3

Network with professionals in the energy and AI fields. Attend industry events or webinars to connect with potential colleagues and learn more about the challenges and innovations in the sector, which can give you an edge in interviews.

✨Tip Number 4

Demonstrate your problem-solving skills by preparing examples of how you've tackled complex issues in previous roles. Highlight your practical approach to implementing AI solutions, as this is crucial for the fast-paced environment at Fuse Energy.

We think you need these skills to ace Applied AI Engineer

Backend Engineering
Applied AI
Machine Learning
Python Programming
AI/ML Libraries (TensorFlow, PyTorch)
Large-Scale Model Deployment (LLM/VLM)
Cloud Technologies
Containerization
Scalable AI Applications
Integration of AI/ML Models
Problem-Solving Skills
Cloud-Based Platforms (AWS)
Energy Markets Knowledge
Trading Strategies
Weather Forecasting
Demand Patterns Analysis
Data Handling and Processing
Natural Language Processing (NLP) Exposure
Data Engineering Practices

Some tips for your application 🫡

Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications required for the Applied AI Engineer position at Fuse Energy. Tailor your application to highlight relevant experiences and skills that align with their needs.

Highlight Relevant Experience: In your CV and cover letter, emphasise your experience as a Backend Engineer and any practical applications of AI or machine learning you've worked on. Mention specific projects or technologies that relate to the job description, such as Python programming or AI/ML libraries.

Showcase Problem-Solving Skills: Fuse Energy is looking for someone with strong problem-solving abilities. Include examples in your application where you've successfully implemented AI solutions or optimised processes, particularly in fast-paced environments.

Express Enthusiasm for the Energy Sector: Demonstrate your interest in the energy market and how AI can enhance consumer experiences. Mention any relevant knowledge or experience you have in energy trading strategies, demand forecasting, or related fields to show your passion for the industry.

How to prepare for a job interview at Fuse Energy

✨Showcase Your Technical Skills

Make sure to highlight your experience as a Backend Engineer, especially your programming skills in Python and familiarity with AI/ML libraries like TensorFlow or PyTorch. Be prepared to discuss specific projects where you've applied these skills, particularly in relation to AI-driven solutions.

✨Demonstrate Your Understanding of AI Applications

Familiarise yourself with how AI can enhance consumer experiences in the energy sector. Be ready to discuss examples of AI features you would consider implementing, such as personalised energy recommendations or automated onboarding processes.

✨Discuss Collaboration Experience

Since the role involves working closely with backend engineers and data scientists, be prepared to share examples of past collaborations. Highlight how you’ve integrated AI models into real-world applications and improved workflows through teamwork.

✨Stay Updated on Industry Trends

Research the latest advancements in applied AI and machine learning, particularly in the energy sector. Being able to discuss current trends and how they could be applied at Fuse Energy will show your enthusiasm and commitment to the field.

Applied AI Engineer
Fuse Energy
Location: London

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