MLOps Engineer - AI Infrastructure & DeploymentLondon, United KingdomMay 14, 2026Full TimeApply Now### Job DescriptionLocation: London, UK Work Model: On-site Role Type: Full-TimeWe are looking for an MLOps Engineer with strong experience in AI infrastructure and machine learning deployment to join our client’s on-site team in London.This role focuses on building scalable MLOps platforms and deployment pipelines that enable reliable, efficient, and production-ready machine learning systems.—### What You’ll Do* Design and maintain MLOps infrastructure supporting machine learning lifecycle management* Build CI/CD pipelines for training, testing, deployment, and monitoring of ML models* Deploy and manage machine learning workloads in cloud environments* Automate model versioning, retraining, and performance monitoring workflows* Collaborate with data scientists and engineering teams to productionise AI systems* Improve scalability, observability, and reliability of ML

platforms* Implement Infrastructure as Code and automation best practices—### What We’re Looking For#### Required Skills & Experience* Strong experience with MLOps workflows and AI infrastructure* Experience with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure* Experience with containerisation using Docker and orchestration via Kubernetes* Strong Python and automation skills* Experience with CI/CD pipelines and Infrastructure as Code* Familiarity with monitoring and observability tools—#### Nice to Have* Experience with feature stores and experiment tracking* Familiarity with GenAI and LLM deployment workflows* Experience with distributed ML training systems* Knowledge of model governance and AI compliance practices—Location: London, UK Work Model: On-site Role Type: Full-Time

ML platforms* Implement Infrastructure as Code and automation best practices—### What We’re Looking For#### Required Skills & Experience* Strong experience with MLOps workflows and AI infrastructure* Experience with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure* Experience with containerisation using Docker and orchestration via Kubernetes* Strong Python and automation skills* Experience with CI/CD pipelines and Infrastructure as Code* Familiarity with monitoring and observability tools—#### Nice to Have* Experience with feature stores and experiment tracking* Familiarity with GenAI and LLM deployment workflows* Experience with distributed ML training systems* Knowledge of model governance and AI compliance practices—Location: London, UK Work Model: On-site Role Type: Full-Time #J-18808-Ljbffr