At a Glance
- Tasks: Design and develop AI features to enhance consumer energy experiences and streamline internal operations.
- Company: Join a forward-thinking renewable energy startup on a mission to revolutionise energy systems.
- Benefits: Competitive salary, equity bonus, fully expensed tech, and paid annual leave.
- Other info: Dynamic team environment with opportunities for growth and innovation.
- Why this job: Make a real impact in the energy sector while working with cutting-edge AI technology.
- Qualifications: 3+ years engineering experience, strong Python skills, and interest in applied AI.
The predicted salary is between 60000 - 80000 £ per year.
Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $100M from top-tier investors and are creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations.
We're also building the Energy Network: a decentralised platform of smart devices that rewards users in Energy Dollars for electrifying their homes, shifting usage to off-peak hours, and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centres and other energy-intensive industries.
As an Applied AI Engineer, this position is ideal for someone 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. You'll be working 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).
Responsibilities
- Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models.
- 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.
Minimum Requirements
- 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.
Competitive salary and an equity sign-on bonus. Biannual bonus scheme. Fully expensed tech to match your needs. Paid annual leave. Breakfast and dinner for office-based employees.
Remote Applied AI Engineer employer: Fuse Energy
Fuse Energy is an exceptional employer for those passionate about renewable energy and applied AI, offering a dynamic work culture that fosters innovation and collaboration. With competitive salaries, equity bonuses, and a commitment to employee growth through exciting projects, team members can thrive in a supportive environment while contributing to a mission that aims to revolutionise the energy sector. Located remotely, employees enjoy flexibility and the opportunity to work on cutting-edge technology that directly impacts consumer experiences and enhances operational efficiency.
StudySmarter Expert Advice🤫
We think this is how you could land Remote Applied AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the renewable energy and AI sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there. You never know who might have a lead on that perfect Applied AI Engineer role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to energy or automation. This will give potential employers a taste of what you can do and how you can contribute to their mission at Fuse Energy.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and understanding of the energy market. Be ready to discuss how your experience aligns with Fuse's goals and how you can leverage AI to enhance consumer experiences.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in being part of our innovative team at Fuse Energy.
We think you need these skills to ace Remote Applied AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Applied AI Engineer role. Highlight your backend engineering experience and any projects related to AI or machine learning that you've worked on.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about renewable energy and how your skills can contribute to our mission. Be specific about your interest in applied AI and how it can enhance customer experiences.
Showcase Your Projects:If you've worked on relevant projects, whether personal or professional, make sure to include them. We love seeing practical applications of AI, especially if they relate to energy or automation.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role!
How to prepare for a job interview at Fuse Energy
✨Know Your AI Stuff
Make sure you brush up on your applied AI and machine learning knowledge. Be ready to discuss specific projects you've worked on, especially those involving Python and AI libraries like TensorFlow or PyTorch. This will show that you’re not just familiar with the concepts but have practical experience too.
✨Understand the Energy Sector
Familiarise yourself with the renewable energy landscape, particularly how AI can enhance consumer experiences and operational efficiency. Knowing about energy markets, trading strategies, and demand forecasting will give you an edge and demonstrate your genuine interest in Fuse Energy's mission.
✨Showcase Collaboration Skills
Since this role involves working closely with backend engineers and data scientists, be prepared to share examples of how you've successfully collaborated in the past. Highlight any cross-functional projects where you integrated AI solutions, as this will illustrate your teamwork abilities and adaptability.
✨Stay Current with Trends
Keep up with the latest advancements in applied AI and machine learning. During the interview, mention recent developments or tools that excite you and how they could be applied at Fuse Energy. This shows that you're proactive and passionate about leveraging cutting-edge technology in your work.
