Salary: £100,000 - 100,000 per year Requirements: Mastery of Python with a heavy focus on software engineering best practices (Design Patterns, Clean Code, Unit Testing) Familiarity with C++ or Go is a significant plus Deep experience with containerization (Docker, Kubernetes) and orchestration tools like Kubeflow, Airflow, or Metaflow Expertise in deploying ML workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask) 5 years in a software or data engineering role, with at least 3 years specifically focused on the deployment and scaling of Machine Learning models A degree in Computer Science, Software Engineering, or a related technical field Systems thinking with a focus on Responsibilities: Design and implement the end-to-end lifecycle of ML models, including automated retraining, model versioning, and monitoring systems Take validated prototypes from our Data Science team and re-engineer them into high-performance, maintainable codebases that integrate seamlessly with client ecosystems Build and maintain CI/CD pipelines specifically for machine learning, ensuring that deployments are predictable, reproducible, and secure Profile and optimize model inference latency and memory usage to ensure applications remain responsive under heavy load Work at the intersection of Data Science and DevOps, ensuring that the science translates into a stable product. Technologies: AI Airflow AWS Azure CI/CD DevOps Docker GCP Kubeflow Kubernetes Machine Learning Python Security Spark Cloud More: We are looking for a Senior Machine Learning Engineer to build the infrastructure and pipelines that power our AI solutions. In this full-time, permanent role based in London with a hybrid work option, you will create robust, scalable, and automated systems that ensure our models perform in high-pressure production environments across various industries. We value reliability, automation, and a security mindset in our team, and were excited to find someone who shares our commitment to these principles. last updated 17 week of 2026