Location: London (Hybrid – 2-3 days/week onsite) Contract Length: 6 months initially (with likely extension) Type: Contract Day Rate: Competitive – Dependent on Experience Start Date: ASAP / July start ideal We are currently hiring on behalf of a confidential EnergyTech company that plays a pivotal role in the UK’s energy infrastructure. They are a top-tier supplier and analytics provider, supporting grid-level energy forecasting, renewables integration, and carbon reduction initiatives. With deep partnerships across government and the private sector, they are recognised as a leader in smart energy optimisation and predictive systems. As they continue to expand their AI capabilities, they’re seeking a Machine Learning Engineer to help productionise ML models and deliver real-time insights across their energy analytics platforms. Key Responsibilities: • Develop, deploy, and monitor robust ML systems for energy usage prediction and optimisation • Work on large-scale time-series datasets to improve model accuracy and stability • Collaborate with Data Scientists and DevOps to build end-to-end ML pipelines • Contribute to model governance, MLOps, and performance monitoring frameworks • Participate in code reviews, design discussions, and performance tuning Requirements: • 3+ years of experience in a Machine Learning Engineer or similar role • Proficiency in Python, ML frameworks (TensorFlow, PyTorch), and deployment tools (Docker, MLflow, etc.) • Experience building scalable ML pipelines in cloud environments (AWS, GCP or Azure) • Familiarity with energy systems, smart metering, or IoT data is a significant bonus • Bachelor’s or Master’s degree in Computer Science, Engineering, Machine Learning, or a related discipline • Strong problem-solving mindset and ability to work cross-functionally in agile teams