26 to 47 of 47 MLOps Jobs in the North of England

evaluation of new model architectures. · Implement production features end-to-end under guidance from senior engineers. · Participate in code reviews, testing, deployment, and MLOps workflows. · Work across internal products and contract-based venture projects. Requirements · Strong foundational programming skills in Python. · Basic understanding of AI/ML models ...

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people … opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps ...

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people … opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps ...

maintain scalable, end‐to‐end AI/ML pipelines using Microsoft Fabric Develop, train, deploy and monitor machine learning and deep learning models Implement MLOps best practices including versioned data and features, CI/CD pipelines, model promotion and rollback. Collaborate with data scientists, analytics engineers, product managers and software … generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). Commercial exposure to e‐commerce, travel or holiday‐lettings environments. Experience mentoring others or leading technical ...

maintain scalable, end‐to‐end AI/ML pipelines using Microsoft Fabric Develop, train, deploy and monitor machine learning and deep learning models Implement MLOps best practices including versioned data and features, CI/CD pipelines , model promotion and rollback . Collaborate with data scientists, analytics engineers, product managers … generation Knowledge of AutoML, hyperparameter optimisation and advanced MLflow features. Experience working with streaming or real‐time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker). Commercial exposure to e‐commerce, travel or holiday‐lettings environments. Experience mentoring others or leading technical ...

using Azure Key Vault and Azure AD. Ensure connectivity between on-prem services and Azure cloud infrastructure using GreenLink and hybrid networking. Collaborate with MLOps and Data Engineers to ensure reproducible, reliable, and auditable infrastructure across environments. Monitor system health, logging, and metrics using platform observability tools (e.g. Azure Monitor ...

production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. You'll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This … navigating the intersection of research, engineering, and product delivery. Roles & Responsibilities: Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. Collaborate with Research, Product, and Infrastructure teams ...

production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. You'll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This … navigating the intersection of research, engineering, and product delivery. Roles & Responsibilities: Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. Collaborate with Research, Product, and Infrastructure teams ...

production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. You'll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing's AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. This … navigating the intersection of research, engineering, and product delivery. Roles & Responsibilities: Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. Collaborate with Research, Product, and Infrastructure teams ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

teams Build and maintain end-to-end ML pipelines (training, validation, inference, monitoring) Ensure models meet requirements around performance, resilience, and explainability Contribute to MLOps best practices, model governance, and technical standards Support model monitoring, drift detection, and ongoing optimisation Required Experience Proven commercial experience as a Machine Learning Engineer … with cloud platforms (AWS, GCP, or Azure) Nice to Have Experience with fraud, risk, credit, AML, pricing, or customer analytics use cases Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, etc.) Docker and Kubernetes experience Exposure to model governance, explainability, or regulatory frameworks Contract Details £650–£750 per day (Outside IR35 ...

ML Engineer Location: Chester (Hybrid - 2x week in office) Salary: £70,000 - £80,000 About the Role I'm working with an established company who are looking to bring an ML Engineer into their team. ...

ML Engineer Location: Chester (Hybrid - 2x week in office) Salary: £70,000 - £80,000 About the Role I'm working with an established company who are looking to bring an ML Engineer into their team. ...

research and implementation, taking models from concept to production, setting technical standards and supporting junior engineers. The role involves close collaboration with the AI, MLOps and Data Engineering teams, contributing to the wider technical strategy and ensuring models are reliable, maintainable and scalable. Key Responsibilities Design and develop … Carry out analysis to understand model behaviour, drift and explainability. Build and maintain tools for evaluation, prompt testing and dataset preparation. Work with the MLOps engineer to deploy, monitor and retrain models in production. Support CI/CD processes for AI, including version control, reproducibility and rollback workflows. Provide mentorship ...

research and implementation, taking models from concept to production, setting technical standards and supporting junior engineers. The role involves close collaboration with the AI, MLOps and Data Engineering teams, contributing to the wider technical strategy and ensuring models are reliable, maintainable and scalable. Key Responsibilities Design and develop … Carry out analysis to understand model behaviour, drift and explainability. Build and maintain tools for evaluation, prompt testing and dataset preparation. Work with the MLOps engineer to deploy, monitor and retrain models in production. Support CI/CD processes for AI, including version control, reproducibility and rollback workflows. Provide mentorship ...

research and implementation, taking models from concept to production, setting technical standards and supporting junior engineers. The role involves close collaboration with the AI, MLOps and Data Engineering teams, contributing to the wider technical strategy and ensuring models are reliable, maintainable and scalable. Key Responsibilities Design and develop … Carry out analysis to understand model behaviour, drift and explainability. Build and maintain tools for evaluation, prompt testing and dataset preparation. Work with the MLOps engineer to deploy, monitor and retrain models in production. Support CI/CD processes for AI, including version control, reproducibility and rollback workflows. Provide mentorship ...

MLOps Engineer AWS SageMaker Contract Length: Initial 8-week contract Location: Remote Security Clearance: SC Clearance £500pd - £550pd (Inside IR35) Role Overview We are seeking an experienced MLOps Engineer with strong expertise in AWS SageMaker to support the delivery, deployment, and operationalisation of machine learning models. This is a short … term contract role, ideal for someone who can hit the ground running in a fast-paced environment. Key Responsibilities Design, build, and maintain MLOps pipelines using AWS SageMaker Deploy, monitor, and manage machine learning models in production Automate model training, testing, and deployment workflows Ensure scalability, reliability, and security ...