17 of 17 Azure Machine Learning Jobs in the North of England

title: Machine Learning Engineer Locations: Manchester or Haywards Heath (hybrid working) Role overview Markerstudy Group are looking for a Machine Learning Engineer to help take leading-edge and novel insurance risk modelling and pricing techniques and participate in creating fully automated machine learning pipelines. Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1 billion. Most of Markerstudy's business ...

Design, train, and deploy production-grade ML models. About the Role As a Senior Machine Learning Engineer, you will lead the design, development, and deployment of production-grade machine learning systems for global enterprise clients. You'll work at the intersection … feature stores and data pipelines Stay current with latest ML research and evaluate applicability to client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale ...

Role: As a Senior AI/ML Engineer, you’ll play a pivotal role in designing, building, and deploying scalable AI and machine learning solutions across Forge Holiday Group. From data pipelines to machine learning models, your work will power customer interactions … decision-making. You’ll Own: Build and maintain end-to-end AI/ML pipelines in Microsoft Fabric Design, train, deploy, and monitor machine learning and deep learning models Implement MLOps best practices: versioned data & features, CI/CD pipelines, model promotion, and rollback ...

available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Manchester Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … outcomes. Experienced in securing work through RFI/RFPs, bids, and presentations across public and private sectors. Skilled in data science platforms (e.g. Databricks, AzureML) and cloud services (AWS, Azure, GCP), with knowledge of tools like Terraform. Experienced in deploying solutions using Docker, Kubernetes, CI/ ...

stakeholders to design and deliver solutions to complex problems. Develop and expand Data Science capabilities and support capability building within the organisation. Manage machine learning deployment pipelines (MLOps) and resolve potential bottlenecks. Mentor and coach other engineers to support their professional development. About the Candidate Extensive … experience in Python and proficiency in other languages (e.g., SQL, R, Java). Strong experience deploying and monitoring machine learning (MLOps) using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning. Proven track record of delivering high-quality, scalable data ...

experienced AI Security Engineering Lead to design and deliver the secure engineering patterns, controls, and tooling that protect our AI and machine learning systems.This is a hands-on technical leadership role, where you will take ownership of complex problem spaces and lead through engineering expertise. … DevSecOps environment.Strong expertise securing AI and ML systems at scale, including model lifecycle security, data pipelines, and secure deployment.Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).Solid understanding ...

experienced AI Security Engineering Lead to design and deliver the secure engineering patterns, controls, and tooling that protect our AI and machine learning systems.This is a hands-on technical leadership role, where you will take ownership of complex problem spaces and lead through engineering expertise. … DevSecOps environment.Strong expertise securing AI and ML systems at scale, including model lifecycle security, data pipelines, and secure deployment.Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).Solid understanding ...

network planning and assurance, media supply chains and content operations, or software engineering productivity and developer tooling.Strong understanding of major cloud platforms (AWS, Azure or GCP) and their generative AI services, plus the security, data, compliance and operating-model considerations required for enterprise deployment across complex organisations.Exceptional … client leadership forums.The following will be an added advantage:Relevant certifications in cloud and AI (e.g., AWS, Azure or GCP; machine learning or data engineering certifications).Experience establishing responsible AI practices (governance, risk and controls) for generative AI and advanced analytics.Consulting experience leading ...

network planning and assurance, media supply chains and content operations, or software engineering productivity and developer tooling.Strong understanding of major cloud platforms (AWS, Azure or GCP) and their generative AI services, plus the security, data, compliance and operating-model considerations required for enterprise deployment across complex organisations.Exceptional … client leadership forums.The following will be an added advantage:Relevant certifications in cloud and AI (e.g., AWS, Azure or GCP; machine learning or data engineering certifications).Experience establishing responsible AI practices (governance, risk and controls) for generative AI and advanced analytics.Consulting experience leading ...

business adoption. Working closely with IT, operational, commercial, and leadership teams, you will drive practical AI initiatives using Azure, LLMs, machine learning, and AI agents – ensuring solutions are secure, scalable, integrated, and delivering measurable business impact. The organisation is already investing heavily … concepts including VNets, Entra ID, API Gateways, Private Endpoints, and secure integrations Experience working with at least one major enterprise AI cloud platform (Azure preferred) Strong SQL skills and experience working with both structured and unstructured data Experience building AI agents, workflow automation, and tool/ ...

core of the role is hands on delivery. Key Responsibilities Model ownership from start to finish: Design, build, and deploy production grade machine learning models, from problem framing and experimentation through to live deployment and monitoring. Technical depth: Apply strong statistical modelling, ML, and (where relevant … wider data science function approaches tooling, methodology, and model governance. Technical Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems ...

advanced AI systems and solutions. We’re seeking Senior Engineers with deep technical expertise in AI technologies, particularly in areas such as Azure OpenAI, Cognitive Services, prompt engineering, Retrieval‐Augmented Generation (RAG) architectures, vector stores, and API integrations. You’ll be able to demonstrate substantial experience … DevOps preferred). Experience with microservices architecture, RESTful API development, and system integration. Prior experience in financial services or insurance sectors advantageous. Familiarity with AzureML, Databricks, related Azure technologies, Docker, Kubernetes, and containerization is advantageous. Skills: Advanced proficiency in Python, and familiarity with AI frameworks such ...

commercial stakeholders across the business. This is a hands-on mid-level Data Scientist role focused on developing and deploying customer-focused machine learning models. Projects include: Customer segmentation Customer Lifetime Value (CLTV) modelling Demand forecasting Propensity modelling Targeted promotions and campaign optimisation Data Science initiatives … Experience building predictive or customer-focused models A practical and commercially minded approach to Data Science Nice to have: Cloud exposure (GCP or Azure) Experience with Vertex AI or Azure ML THE BENEFITS Up to £50,000 HOW TO APPLY Please register your interest ...

architecture, security, business, engineering, and data teams (data protection, data risks, AI governance) to shape pragmatic, future-facing AI solutions Proven experience with Azure-native services, such as Azure OpenAI, Azure ML, Cognitive Search, Microsoft 365 extensibility, Azure ...

analytics solutions Proven experience designing and evolving enterprise-scale data platforms Deep expertise in cloud-based data and analytics services on the Microsoft Azure platform (e.g. Azure Databricks, Azure ML) Experience shaping proofs of concept and evolving designs into production solutions ...

Node.js, C#, Python, PHP, Scala, Power platform Frontend: React, JavaScript, Typescript, Angular Data: PostgreSQL, Microsoft SQL Server, Mongodb, Apache Cassandra DevOps: AWS, Kubernetes, Azure, Jenkins, Docker, Ansible, Terraform AI: Azure ML Studio, Python, Github Copilot, OpenAI Person specificationMain ResponsibilitiesDelivering secure, reliable and scalable software ...

Node.js, C#, Python, PHP, Scala, Power platform Frontend: React, JavaScript, Typescript, Angular Data: PostgreSQL, Microsoft SQL Server, Mongodb, Apache Cassandra DevOps: AWS, Kubernetes, Azure, Jenkins, Docker, Ansible, Terraform AI: Azure ML Studio, Python, Github Copilot, OpenAI Person specificationMain ResponsibilitiesDelivering secure, reliable and scalable software ...