Head of Engineering - Machine learning startup

At Fuse, we''re building a fully integrated energy company, from developing solar, wind, and hydrogen to power trading and distributed energy installations. We sell directly to energy consumers, cutting out the middleman to reduce costs and pass on savings to customers.
Were also building the Energy Network: a decentralized network of smart devices where users get rewarded in Energy Dollars for electrifying their homes, shifting usage to off-peak hours, and helping balance the grid. The energy network helps the grid achieve energy stability, a crucial requirement for growth of AI data centers and energy intensive industries.As the Head of Engineering (AI) at Fuse Energy, you will lead the development and integration of AI across our platformfrom intelligent forecasting models and optimization algorithms to personalized customer experiences and internal automation.Youll own the engineering strategy for how AI is built, deployed, and scaled across our stack, partnering closely with data science, product, and platform teams.Own the AI engineering roadmap and lead the development of AI-first featuresProductionize ML models, ensuring scalability, performance, and observabilityDesign the infrastructure for deploying and maintaining ML systems in production (e.g., MLOps, CI/CD for ML, model versioning)Build systems that integrate AI into key parts of our stack, such as:Work closely with product and engineering leadership to identify high-impact AI opportunities
- Build and lead a high-performing team of AI engineers
Strong software engineering background with 5+ years of experience, including at least 2 years leading AI/ML engineering teamsDeep experience deploying ML models into production environmentsProficiency in designing scalable data pipelines and real-time inference systemsUnderstanding of modern ML tooling and frameworks (e.g., PyTorch, TensorFlow, MLflow, AWS SageMaker)Strong cross-functional collaboration skills, particularly with data science and product teamsBonusExperience with large language models (LLMs), RAG, or generative AI in productionBackground in MLOps or AI infrastructure at scaleCompetitive salary and a stock options sign-on bonusBiannual bonus schemePaid annual leaveBreakfast and dinner for office based employees#
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