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About the Role
As an Applied AI Engineer, you will leverage your backend engineering expertise and applied AI interest to enhance customer energy experiences and improve internal operations. You will work on consumer-facing features like the Energy Co-Pilot and speedy onboarding using VLM and LLM tools, and develop AI tools to boost team productivity.
Responsibilities
- Design, develop, and deploy AI-powered features for consumer experiences, including personalized energy recommendations and AI model-driven onboarding.
- Build and optimize internal AI tools to enhance company-wide productivity through automation and workflow improvements.
- Collaborate with backend engineers and data scientists to integrate AI-driven features into platforms.
- Partner with trading and operations teams to align AI models with real-time market conditions and energy pricing.
- Enhance AI models to optimize trading strategies by forecasting market shifts using weather and demand predictions.
- Stay current with applied AI and machine learning advancements and apply them to energy sector challenges.
- Monitor the performance of AI tools and models for efficiency and effectiveness.
Requirements
- 3+ years of software engineering experience.
- Proven backend engineering experience with practical applied AI or machine learning experience.
- Strong Python programming skills and familiarity with AI/ML libraries (TensorFlow, PyTorch, etc.).
- Experience with large-scale models (LLMs/VLMs) and deploying AI solutions to 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.
- Experience working with large datasets, particularly for demand and supply forecasting.
- Experience or strong interest in energy markets and trading strategies.
- Understanding of weather forecasting, energy demand patterns, and production modeling.
- Exposure to NLP or related fields.
Skills
- Applied AI
- Machine Learning
- Backend Engineering
- Python
- TensorFlow
- PyTorch
- Large-scale models (LLMs/VLMs)
- Cloud technologies
- Containerisation
- Scalable AI applications
- Large datasets
- Demand forecasting
- Supply forecasting
- Energy markets
- Trading strategies
- Weather forecasting
- Energy demand patterns
- Production modeling
- NLP
Experience Level
- 3+ years of software engineering experience
Salary/Compensations
- Competitive salary
- Eligibility for equity
Benefits
- Biannual bonus scheme
- Fully expensed tech
- Private health insurance
- Breakfast and dinner allowance for office-based employees
About the Company
- Fuse Energy is an energy startup focused on making energy abundant and affordable through first-principles thinking and cutting-edge technology.
- The company has raised over $200M from prominent investors.
- Fuse Energy is building a fully integrated energy company, encompassing solar, batteries, hardware development, grid infrastructure, real-time power trading, AI utilization, and distributed energy installation.
- They sell directly to consumers to reduce costs and pass savings to customers.