Applied AI Engineer
About The Position
Fuse Energy is an energy startup working to make energy abundant and affordable by building an integrated energy company spanning generation projects, hardware, grid infrastructure, real-time power trading, AI, and distributed energy installations. The Applied AI Engineer role is intended for someone with backend engineering depth and a particular interest in applying AI to improve the energy experience for consumers and internal operations. The engineer will develop consumer-facing features such as an Energy Co-Pilot and AI-assisted onboarding using vision-language and large language models, while also building tools to increase productivity across Fuse. The role works with backend engineers, data scientists, trading teams, and operations teams to deploy and improve AI models and applications in the energy domain.
Requirements
- At least 3 years of software engineering experience; requirements vary by role level.
- Backend engineering experience and a strong interest in, and practical experience with, applied AI or machine learning.
- Strong programming skills in Python or a similar language, with familiarity with AI/ML libraries such as TensorFlow or PyTorch.
- Experience working with large-scale models, including LLMs or VLMs, and deploying AI-driven solutions into production.
- Understanding of cloud technologies, containerisation, and building scalable AI applications.
- Ability to integrate AI/ML models into real-world applications with attention to 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 for demand and supply forecasting.
Nice To Haves
- Experience or strong interest in energy markets and trading strategies.
- Understanding of weather forecasting, energy demand patterns, and production modelling.
- Exposure to NLP or related fields.
Responsibilities
- Design, develop, and deploy AI-powered consumer features, including personalised energy recommendations and AI-assisted onboarding using energy bills.
- Build and optimise internal AI tools to improve productivity through automation and workflow enhancements.
- Collaborate with backend engineers and data scientists to integrate AI-driven features into Fuse platforms.
- Work with trading and operations teams to align AI models with real-time market conditions and energy pricing.
- Improve AI models used to optimise trading strategies by anticipating market shifts based on weather and demand forecasts.
- Stay current with developments in applied AI and machine learning and apply them to energy-sector problems.
- Monitor AI tools and model performance to ensure they operate efficiently and effectively.
Benefits
- Competitive salary and eligibility for equity.
- Biannual bonus scheme.
- Fully expensed technology to match employee needs.
- Private health insurance.
- Breakfast and dinner allowance for office-based employees.
- Benefits may vary by location.
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What This Job Offers
Job Type
Full-time
Education Level
No Education Listed
