18 of 18 Azure Machine Learning Jobs in Manchester

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 ...

role where you can make a difference, we’d love to hear from you. We’re on the hunt for a Lead Machine Learning & AI Engineer to join our Data & Analytics function on a 10-month fixed term contract, where you’ll play a pivotal role … implementing and continuously improving the machine learning and AI operations frameworks that bring innovative solutions to life across our organisation. You’ll design and deliver new tools, components of the framework and engineering practices that turn cutting‐edge models into high‐performing, production‐ready systems. ...

best practices Coaching experience Bachelor's or master's degree and/or equivalent professional experience Deep experience and strong understanding of Microsoft Azure, including Azure ML, Azure Stream Analytics, Cognitive Services, Event Hubs, Synapse, and Data Factory Fluency in Python … systems, ensuring model auditability, and optimizing deployment processes. Highest-signal resume keywords Machine Learning Operations (MLOps) Microsoft Azure Python Programming CI/CD Pipelines Coaching and Team Leadership Hard Skills Machine Learning AI Systems Development Data Pipeline Engineering Model ...

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 ...

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: Essential … Experience 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 ...

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. Skills and experience that … needEssential ExperienceExtensive 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 ...

will be responsible for building and maintaining the backend systems and web applications that support the development, testing, deployment, and scaling of our Machine Learning and LLM‐based tools, and for helping to transform these into robust, market‐ready products. We have ambitious plans to grow … negligence, and with a growing practice in family and private client. Fletchers was one of the first consumer law firms to deploy a machine learning tool for legal work (a decision support system for screening incoming cases, launched ...

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. … 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 ...

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. … 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 ...

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 ...

design. All underpinned by technology created with purpose. We’re seeking a AI engineer who can design, build, and operationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The focus of this role is to bridge the gap between AI prototypes and embedding … suitable cloud services across hyperscalars Architecting and implementing Generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, GCP, or AWS. Embedding safety, evaluation, and assurance mechanisms across the AI lifecycle, ensuring solutions are ethical, explainable, and responsible. Translating business ...

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 ...

Contribute to the design and delivery of robust, automated, and scalable Azure and Snowflake data platform components Develop and maintain reusable infrastructure-as-code with Terraform across environments Build and optimize CI/CD pipelines using Azure DevOps and GitHub Actions Implement observability practices … healthcare and insurance Ensure platform compliance, performance, automation, and technical excellence Requirements Extensive experience in platform engineering, with a strong emphasis on Azure-based data solutions Expert-level knowledge of Azure and/or Snowflake services, including Data Factory, Data Lake, Azure ...

Jobtailor is seeking a senior MLOps leader to implement and evolve production ML/AI platforms on Microsoft Azure. You will coach a compact team of MLOps, Analytics and AI Engineers, and collaborate with Data ...

work model, collaborating with engineering and product teams to embed security early in design. The team emphasizes governance, threat modelling, cloud security across Azure/GCP, AI/ML security, #J-18808-Ljbffr ...

engineering experience - for example, working with IaC, Terraform, or similar tooling. Role: * Contribute to the design and delivery of robust, automated, and scalable Azure and Snowflake data platform components. * Develop and maintain infrastructure-as-code using Terraform, ensuring consistency and reusability across environments. * Build and optimise …/CD pipelines using Azure DevOps and GitHub Actions to support rapid, reliable deployments. * Implement observability practices including logging, metrics, and alerting using observability tools. * Collaborate with the Lead Engineer and Architects to align implementation with platform standards and patterns. * Provide technical guidance and mentorship ...