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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - Production AI Systems - **Company:** Talenzon group - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Cloud Computing, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Google Cloud, Backend, Kubernetes, Low Latency, Machine Learning Operations, Software Version Control, Data Pipelines, Docker - **Published:** August 26, 2026 - **Apply:** https://www.collegerecruiter.com/job/2815055479-machine-learning-engineer--production-ai-systems ## About the Role **Required Skills & Experience*** Strong experience in machine learning engineering or applied ML* Proficiency in Python and ML frameworks* Experience with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure* Experience with containerisation using Docker and orchestration via Kubernetes* Experience with model deployment and monitoring---#### **Nice to Have*** Experience with MLOps tools and pipelines* Familiarity with feature stores and model versioning* Experience with real-time inference systems---Location: London, UK Work Model: On-site Role Type: Full-TimeLocation,Experience levelMid-Senior level## Work Location #J-18808-Ljbffr ## Description # Machine Learning Engineer - Production AI Systems,April 21, 2026### Job Description**Location:** London, UK **Work Model:** On-site **Role Type:** Full-TimeWe are looking for a **Machine Learning Engineer** with strong experience in deploying and scaling machine learning models to join our client's on-site team in London.This role focuses on taking machine learning models from experimentation to production, ensuring they are scalable, reliable, and integrated into real-world applications.---### **What You'll Do*** Deploy and maintain machine learning models in production environments* Build and optimise data pipelines for training and inference workflows* Collaborate with data scientists to productionise models* Monitor model performance and implement retraining pipelines* Improve scalability, latency, and reliability of ML systems* Integrate ML services into backend applications via APIs* Implement MLOps best practices across the ML lifecycle---### **What We're Looking For**#### **Required Skills & Experience*** Strong experience in machine learning engineering or applied ML* Proficiency in Python and ML frameworks* Experience with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure* Experience with containerisation using Docker and orchestration via Kubernetes* Experience with model deployment and monitoring---#### **Nice to Have*** Experience with MLOps tools and pipelines* Familiarity with feature stores and model versioning* Experience with real-time inference systems---Location: London, UK Work Model: On-site Role Type: Full-TimeLocation,Experience levelMid-Senior level## Work Location ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) ## Related Articles - [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 – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [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)