51 to 75 of 81 MLOps Jobs in the UK excluding London

as a C# Developer with proficiency in Python, .NET framework and C# as well as experience with ML.NET, ASP.NET, MVC, Web API Containers (Docker/Kubernetes), Machine Learning Operations (MLOps) and CI/CD Good knowledge of IT industry trends (especially GenAI and AgenticAI), suppliers, platforms and products Post productions MLOps, Model retaining and Drift monitoring in Azure with knowledge More ❯

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

will use your skills to: Tune machine learning methods to best leverage our state-of-the-art processing capabilities Deploy and maintain machine learning methods in a DevOps/MLOps based machine learning environment Create robust high-quality code using test-driven development (TDD) techniques and adhering to the SOLID coding standards Your work will enable sustained improvements to products … Head of Data Science, and Head of Technical Underwriting Propose, proof-of-concept, develop, and deliver novel machine learning processes that automate current manual processes, and leverage DevOps and MLOps software. Work in a collaborative environment with data science to help deploy machine learning methods that are state-of-the-art, robust, and future extensible. Tune machine learning methods for … of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google Cloud, etc. Experience with deploying services in Docker and Kubernetes Experience in creating production grade coding and SOLID programming principles More ❯

Job Title: ML Ops/LLM Ops Engineer Location: Hybrid (potentially 1 day per week in east London) Contract: 6 month Contract Day Rate: £400 per day (Outside IR35) About the Role We are seeking an experienced ML Ops/ More ❯

initiatives. Working for a US Sports analytics client you'll collaborate with their technical team, providing advanced mathematical models derived from large datasets and statistics for the client's MLOps team to productionise. Location/WFH: You'll join a friendly and sociable team in the London office two days a week (Mondays and Thursdays) with flexibility to work from More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

diverse modeling techniques, including tree based models, advanced neural networks and hybrid models. ** Skilled in optimisng ML for real time serving think quantization, pruning, and distillation. ** Proficient with modern MLOps practices and tooling, handling everything from model governance to scalable deployment pipelines. ** Comfortable working hands on with Python, GPU acceleration, and distributed computing frameworks. ** A confident communicator and collaborator, able More ❯

Tesco, Sainsbury's, O2, Halifax, AA, Saga and Lloyds Bank to list a few. As a Machine Learning Engineer, you will help build and maintain the pricing team's MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function. Key … Responsibilities: Build an MLOps/DevOps environment to support machine learning automation Build the pipelines that automate the regular model update and monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation … and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and Experience: Previous experience as a DevOps/MLOps engineer Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud) Understanding of machine learning models and the modelling process, from data ingestion and More ❯

experience applying these techniques in production environments. Project Leadership : Proven experience leading complex technical projects, with a track record of successfully evolving existing systems and innovating with new solutions. MLOps & Modern Practices : Strong understanding of modern data science and MLOps practices, including model lifecycle management, experimentation, and CI/CD. Core Programming & Software Craftsmanship : Proficiency in Python and SQL, with More ❯

Role? Shape and deliver the security architecture strategy for enterprise cloud and AI/ML programmes. Work on cutting-edge initiatives in the financial services domain, integrating AI and MLOps with security guardrails. Act as a trusted advisor to senior leadership , influencing both business and technology direction. Key Responsibilities Define and evolve security architecture strategies for cloud, AI/ML … and MLOps environments . Act as a senior security advisor to leadership, engineering, and business stakeholders. Develop security architecture standards, patterns, and guidelines for enterprise solutions, with specific coverage for AI/ML workloads. Conduct security architecture reviews, threat modelling, and risk assessments for AI/ML systems and pipelines . Ensure solutions comply with European financial services regulations (GDPR … PSD2, DORA, NIS2) as well as emerging AI governance frameworks (e.g., EU AI Act, NIST AI RMF). Integrate security into DevSecOps and MLOps pipelines , including CI/CD and infrastructure-as-code environments. Drive adoption of Zero Trust principles, encryption standards, IAM policies, and network/data/application security controls. Collaborate with data scientists, ML engineers, and IT More ❯

needs, and see the real-world impact of your work. What You'll Be Doing Building and deploying production ML pipelines in cloud environments (AWS, Azure, or GCP) Implementing MLOps best practices to maintain and scale AI applications Working directly with NHS trusts and healthcare clients to understand their challenges Contributing to both project delivery and the development of repeatable … learning algorithms and their practical application Ability to deliver high-quality work to tight deadlines Genuine interest in healthcare - you want your work to matter Highly Desirable: Experience with MLOps in cloud environments Background in healthcare, consulting, or research settings Exposure to modern cloud platforms (AWS/Azure/GCP) Salary: £40,000 - £55,000 + good benefits + bonus More ❯

Technical Product Manager - Data, GCP, BigQuery, Cloud, Pyton, CI/CD, MLOps Role Profile Role Title: Technical Product Manager (Dynamic Allocation Services) Reporting To: Head of Product Location: Birmingham/Remote (with occasional travel to customer sites) Summary The Technical Product Manager (Dynamic Allocation Services) is responsible for driving the technical direction, development, and optimisation of our product. Combining product … design into technical specifications. Experience designing or managing decision-support systems, simulations, or optimisation engines. Familiarity with cloud environments (e.g. GCP, BigQuery) and modern deployment practices (CI/CD, MLOps). Product & Delivery Skills Ability to translate complex technical concepts into structured product requirements. Experience in Agile product delivery, backlog management, and sprint planning. Up to 10% discretionary bonus Fully More ❯

Machine Learning Operations Engineer - Remote - 50- 70k + excellent benefits We're looking for a skilled Machine Learning Operations Engineer to join a newly established team working on an exciting data platform project. This is a hands-on role where More ❯

Machine Learning Operations Engineer - Remote - £50-£70k + excellent benefits We're looking for a skilled Machine Learning Operations Engineer to join a newly established team working on an exciting data platform project. This is a hands-on role where More ❯

Overview You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and thought leadership. This is more than a sales-adjacent role - it's your opportunity to shape the future of data & AI consulting and lead from More ❯

JOB VACANCY GLOBAL LOGIC Company: Global Logic Job Title: GTM Solutions Architect, AI/ML - Intelligent Enterprise Location: United Kingdom - Edinburgh, London, Manchester Working style: Hybrid You'll be part of a collaborative, entrepreneurial environment that values innovation, excellence, and More ❯

to join our team in Radbroke. This hybrid role offers the opportunity to work on cutting-edge machine learning and data engineering projects, leveraging the latest cloud technologies and MLOps practices. Required/Primary Skills: AWS Data Engineering ML Engineering ML-Ops ECS, Sagemaker Gitlab Jenkins CI/CD AI Lifecycle Experience in front-end development (HTML, Stream-lit, Flask … with model deployment and monitoring in cloud environments (AWS). Understanding of machine learning lifecycle and data pipelines. Proficiency with Python, Pyspark, Big-data ecosystems Hands-on experience with MLOps tools (e.g., MLflow, Airflow, Docker, Kubernetes) Secondary Skills Experience with RESTful APIs and integrating backend services All profiles will be reviewed against the required skills and experience. Due to the More ❯

e.g. ISO27001, GDPR, DCC) Actively promote team values and adhere to all relevant company policies DevOps Responsibilities: Implement and manage DevOps pipelines for AI and computer vision products Integrate MLOps practices for data versioning, experiment tracking and model deployment Collaborate with the Technology team to ensure DevOps workflows accelerate product delivery and support Ensure strong data management, storage and backup …/CD pipeline design and automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Familiarity with GPU based computer environments Familiarity with MLOps and associated tooling Familiarity with data pipelines Familiarity with Infrastructure as Code Familiarity with security integration in DevOps i.e. DevSecOps Essential Tools: Ubuntu and Red Hat Linux Windows 365 environment More ❯

e.g. ISO27001, GDPR, DCC) Actively promote team values and adhere to all relevant company policies DevOps Responsibilities: Implement and manage DevOps pipelines for AI and computer vision products Integrate MLOps practices for data versioning, experiment tracking and model deployment Collaborate with the Technology team to ensure DevOps workflows accelerate product delivery and support Ensure strong data management, storage and backup …/CD pipeline design and automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Familiarity with GPU based computer environments Familiarity with MLOps and associated tooling Familiarity with data pipelines Familiarity with Infrastructure as Code Familiarity with security integration in DevOps i.e. DevSecOps Essential Tools: Ubuntu and Red Hat Linux Windows 365 environment More ❯

e.g. ISO27001, GDPR, DCC) Actively promote team values and adhere to all relevant company policies DevOps Responsibilities: Implement and manage DevOps pipelines for AI and computer vision products Integrate MLOps practices for data versioning, experiment tracking and model deployment Collaborate with the Technology team to ensure DevOps workflows accelerate product delivery and support Ensure strong data management, storage and backup …/CD pipeline design and automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Familiarity with GPU based computer environments Familiarity with MLOps and associated tooling Familiarity with data pipelines Familiarity with Infrastructure as Code Familiarity with security integration in DevOps i.e. DevSecOps Essential Tools: Ubuntu and Red Hat Linux Windows 365 environment More ❯

Lead Machine Learning Operations Engineer - Remote - 70- 90k + Excellent Benefits We're seeking a Lead Machine Learning Operations Engineer to spearhead the development and optimisation of our cutting-edge data platform. This is a strategic, hands-on leadership role More ❯