MLOps Engineer – AI Infrastructure & Deployment

Talenzon group; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

Talenzon group is seeking an MLOps Engineer to join their team in London. This role focuses on designing and maintaining MLOps infrastructure to support machine learning lifecycle management. You will build CI/CD pipelines for training, testing, and deployment of ML models, working closely with data scientists to ensure reliability and efficiency.

The ideal candidate will have strong experience with MLOps workflows, cloud platforms, and automation using Python. Join us to help scale innovative AI systems!

Qualifications

• Strong experience with MLOps workflows and AI infrastructure.
• Experience with cloud platforms like AWS, Google Cloud, or Microsoft Azure.
• Strong Python and automation skills.

Responsibilities

• Design and maintain MLOps infrastructure for machine learning lifecycle management.
• Build CI/CD pipelines for deployment, training, and testing of ML models.
• Collaborate with teams to productionise AI systems.

Skills

MLOps workflows

Cloud platforms (AWS, GCP, or Azure)

Containerisation (Docker)

Orchestration (Kubernetes)

Python

CI/CD pipelines

Infrastructure as Code

Monitoring tools

Job 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