MLOps Engineer London, 3 days per week on site, £100,000 to £110,000 plus discretionary bonusThis is a great opportunity if you want to own real MLOps in a modern AWS environment, work with production ML models at scale, and see your work directly contribute to the clean energy transition. You will have the autonomy to shape how models are built, deployed and monitored, while still learning from experienced engineers around you. The Company They are a fast-growing cleantech scale-up using data and AI to make electric vehicle charging smarter and more sustainable. Their intelligent energy platform connects vehicles, chargers, customers and energy providers to optimise how and when energy is used. They are operating across multiple countries and are backed by strong industry partnerships. You will join a close-knit Data function that is central to their mission and product roadmap. The Role In this MLOps Engineer role, you will be at the heart of how machine learning is delivered into production. You will: * Design, build and maintain scalable ML pipelines for training, validation and deployment. * Set up and manage MLflow or similar tools so experiments, models and results are fully tracked and reproducible. * Deploy, manage and monitor ML and AI endpoints in AWS, with a strong focus on SageMaker. * Implement and improve CI/CD practices for ML workloads to ensure reliable, repeatable releases. * Work closely with Data Engineers, AI Engineers and other stakeholders to productionise models and A/B/X test them. * Enhance infrastructure for performance, cost efficiency and reliability, using containerisation and Infrastructure as Code. * Help shape MLOps standards and best practices as the company and platform scale. Your Skills & Experience You will be a good fit for this MLOps Engineer position if you have: * Strong commercial experience programming in Python for ML and data products. * Proven hands-on experience with MLOps practices, including MLflow (or similar), model versioning, and monitoring. * Solid expertise with AWS, particularly building and deploying models using SageMaker. * Good understanding of cloud and DevOps principles, including Docker and Infrastructure as Code (ideally AWS CDK). * Experience deploying and managing different types of ML models, for example image recognition and other ML workloads. * A mindset focused on reliability, scalability and clean engineering practices. * A collaborative, proactive approach and genuine interest in working in a fast-paced, office-based team environment. What They Offer * Salary of £100,000 to £110,000 plus discretionary bonus. * Hybrid working with three days per week in a central London office. * The chance to shape MLOps in a growing Data team and have clear impact on product and strategy. * Exposure to modern AWS tooling and the opportunity to work on a variety of ML use cases. * Benefits including private health insurance, pension and other flexible perks Apply with your CV below!