About the Role
The company is an energy startup on a mission to make energy abundant and affordable, fast. We are building a fully integrated energy company that develops solar technology, batteries, and other generation projects, while improving and developing grid infrastructure. As part of our cutting-edge AI team, we are seeking an Applied AI Engineer. This role is ideal for someone with the technical expertise of a backend engineer who has a keen interest in applied AI and its potential to enhance the energy experience for both customers and internal operations. You will work on consumer features such as the Energy Co-Pilot and improve onboarding using VLM and LLM tools, while also developing AI tools that boost productivity across the company.
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Responsibilities
- Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalized energy recommendations and seamless onboarding via AI models (e.g., using energy bills for quick setup)
- Build and optimize internal AI tools that enhance company productivity, with a focus on automation and improving workflows
- Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms
- Work 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 anticipating market shifts based on weather and demand forecasts
- Stay updated on the latest advancements in applied AI and machine learning, applying them to real-world energy challenges
- Monitor the performance of AI tools and models to ensure optimal efficiency and effectiveness
Requirements
- 3+ years of software engineering experience, with requirements varying by role level
- Proven experience as a backend engineer with strong interest and practical experience in applied AI or machine learning
- Strong programming skills in Python (or similar) 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, containerization, and building scalable AI applications
- Ability to integrate AI/ML models into real-world applications, focusing on usability and performance
- Strong problem-solving capabilities and a practical approach to implementing AI solutions in a fast-paced environment
- Experience with large datasets, particularly related 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 modeling; exposure to NLP or related fields
Benefits
- Competitive salary and eligibility for equity
- Biannual bonus scheme
- Fully expensed technology to match your needs
- Private health insurance
- Breakfast and dinner allowance for office-based employees
As we hire globally, benefits may vary by location.
