> Markdown version of [/jobs/ext/2244078-mlops-engineer-ai-infrastructure-deployment](https://www.wearedevelopers.com/jobs/ext/2244078-mlops-engineer-ai-infrastructure-deployment). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# MLOps Engineer - AI Infrastructure & Deployment

- **Company:** Talenzon group
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Monitoring of Systems, Python (Programming Language), Machine Learning, Azure Machine Learning, AI Infrastructure, Google Cloud, Delivery Pipeline, Large Language Models, Containerization, Kubernetes, Performance Monitor, Machine Learning Operations, Software Version Control, Docker
- **Published:** August 26, 2026
- **Apply:** https://www.collegerecruiter.com/job/2815168151-mlops-engineer--ai-infrastructure--deployment

## About the Role

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

## Description

# MLOps Engineer - AI Infrastructure & DeploymentLondon, United KingdomMay 14, 2026Full TimeApply Now### Job Description**Location:** 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


## Related Videos

- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way)
- [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills)
- [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops)
- [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes)
- [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker)

## Related Articles

- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)