26 to 50 of 76 Azure Machine Learning Jobs in London

phases or proof‐of‐concept work. Support the design and delivery of Generative AI solutions, including RAG architectures, prompt engineering, and integration with Azure AI services (e.g., Azure OpenAI, Azure AI Search). Ensure robust MLOps practices are followed, including model … deployed solutions. Cloud platform experience, preferably Azure, including services such as Azure OpenAI, Azure Machine Learning, or Azure AI Search. Experience managing or leading technical delivery teams, with a track record of fostering ...

Azure AI ecosystem — including Azure OpenAI, Azure AI Studio, and Azure Machine Learning Experience building and running production-grade AI systems on cloud infrastructure (APIs, event-driven architectures, scalable compute such … medical care scheme Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role #J-18808-Ljbffr ...

Data Scientist to join a high-performing Analytics & Data Science team. This is an opportunity to work at the forefront of Data Science, Machine Learning, Agentic AI and Generative AI, helping major organisations unlock value from their data and solve complex business challenges. You'll collaborate … role in delivering innovative solutions across a diverse project portfolio What You’ll Do: Develop and deploy advanced analytics, data science, machine learning and agentic ai solutions across a variety of use cases Use technologies such as Python, R, Azure, Databricks, SQL, Power ...

challenges! It would be great if you also had experience in some of these, but if not well help you with them Machine Learning softwaree.g. Amazon and Azure machine learning, or Google'sTensorFlow Deploying and managing in Cloud Computing … dedicated Career Manager to help you develop your career and guide you on your journey through BAE Dont know a particular technology? Your learning and development is key to your future career and we provide a range of excellent training courses to enable you to upskill ...

practice focuses on helping clients control their data, turn it into actionable insights, and better leverage it through the use of AI and Machine Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/… scale. Strong opinions on secure, resilient enterprise deployment of LLM‐powered systems; current knowledge of the latest model capabilities and AI product stacks. Machine Learning Engineering End-to‐end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. ...

automating manual processes across the business, and you'll be working directly with underwriters and the actuarial team throughout. Stack is Python and Azure, with a strong emphasis on engineering and MLOps standards. There's also scope to bring generative AI into the roadmap. You'll coach … standard, with object oriented design, testing and code review as standard practice Models you've personally taken into production and supported in life Machine learning across the usual toolkit: scikit-learn, pandas, NumPy, statsmodels or similar MLOps and CI/CD in practice. Pipeline orchestration, model ...

Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field — or equivalent professional experience.· Strong knowledge of generative AI, machine learning, deep learning, natural language processing and other relevant AI fields.· Proven track record of designing, developing, and deploying AI systems … Jira and Confluence.· Exceptional leadership and communication skills, with the ability to convey complex technical concepts to diverse audiences.· Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous.· Professional accounting qualification preferred, however not a requirement.Why Audit at KPMG Audit ...

DescriptionCertificationsNVIDIA certifications (NCP-AI Infrastructure, or NVIDIA Deep Learning Institute credentials) — strongly preferred.Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer — at least … equivalent demonstrable experience.Advanced degree (MS in CS/AI/ML or related) beneficial but not required given sufficient hands-on depth.Continuous, demonstrable learning in AI — publications, open-source contributions, conference speaking, or lab-based experimentation are all valued signals.Job RequirementsEnterprise Architect — Artificial IntelligenceAI/ML Infrastructure, Platform ...

data integration and relational platforms. Proven experience designing highly available Hybrid and Multi-Cloud architectures (Azure & AWS). AI & Machine Learning Exposure: Experience designing architectures that support AI/ML workloads, including integrating Large Language Models (LLMs), predictive analytics, and vector search into … NFRs) such as scalability, maintainability, performance, latency, and security. AI Strategy & Adoption AI Architecture Roadmap: Lead the architectural design for integrating AI and Machine Learning capabilities (including Generative AI) into existing and new enterprise products. AI Governance & Security: Establish secure guardrails, data privacy controls, and ethical ...

data integration and relational platforms Proven experience designing highly available Hybrid and Multi-Cloud architectures (Azure & AWS). AI & Machine Learning Exposure: Experience designing architectures that support AI/ML workloads, including integrating Large Language Models (LLMs), predictive analytics, and vector search into … NFRs) such as scalability, maintainability, performance, latency, and security. AI Strategy & Adoption AI Architecture Roadmap: Lead the architectural design for integrating AI and Machine Learning capabilities (including Generative AI) into existing and new enterprise products. AI Governance & Security: Establish secure guardrails, data privacy controls, and ethical ...

DescriptionCertificationsNVIDIA certifications (NCP-AI Infrastructure, or NVIDIA Deep Learning Institute credentials) — strongly preferred. Cloud AI/ML certification: AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate, or Google Professional Machine Learning Engineer — at least … experience. Advanced degree (MS in CS/AI/ML or related) beneficial but not required given sufficient hands-on depth. Continuous, demonstrable learning in AI — publications, open-source contributions, conference speaking, or lab-based experimentation are all valued signals. Job RequirementsEnterprise Architect — Artificial IntelligenceAI/ML Infrastructure ...

easily simplify complex concepts for senior decision‐makers Strong technical command of modern cloud infrastructure (GCP, AWS, Azure) and machine learning concepts A "hacker mindset" with a strong engineering foundation: you are a creative problem‐solver who builds robust, scalable, and efficient scripts … cloud platform (GCP, AWS, or Azure), including data storage, compute, and deployment patterns common in ML workflows Solid understanding of machine learning concepts and the ML development lifecycle — from data preparation and annotation through model training, evaluation, and deployment Demonstrated ability to lead ...

knowledge representation, and agentic AI), ensuring reliable, scalable operation across a growing base of local authority clients. Deploy and manage ML models via Azure ML endpoints, batch endpoints, and AKS, enabling resilient, secure model hosting that accelerates client onboarding and ensures models remain performant and monitorable throughout … MLOps, Platform Engineering, or Infrastructure Engineering role supporting ML or data‐intensive systems. Strong programming skills and production experience in Python. Expertise in Azure‐native MLOps, including model endpoints, pipelines, registries, environments, and compute management. Clear evidence of practical experience across the following: Deploying, scaling, and troubleshooting ...

Hybrid Job Type: FTE We are seeking a highly experienced AI Consultant to design, implement, and drive enterprise-grade AI solutions on the Azure platform Microsoft AI Foundry. This role combines hands‐on experience, solution architecture, and technical leadership, with responsibility for guiding teams and proactively supporting … with Azure AI Search (vector and hybrid search), Azure AI Document Intelligence, and Azure Machine Learning. Ability to wire these services together into coherent, production‐ready architectures not just run individual demos. Understanding of Azure security ...

/ranking quality, and knowledge graph aware retrieval while enforcing content rights and confidentiality.Key ResponsibilitiesML & LLM Engineering, Search and Recommendation EnginesAutomate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI) Maintain … MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala engineering Experience with statistical analysis, machine learning theory and natural language processing Hands on experience with major cloud vendor solutions (AWS, Azure and/ ...

startup-like culture nurtured by sports and social clubs, being a safe place to fail, meaning and self-fulfilment over business, and learning from our partners, suppliers, and peers.We fully embrace DevOps ways of working in our teams, and build a very broad range of capabilities … challenges!It would be great if you also had experience in some of these, but if not we’ll help you with themMachine Learning software e.g. Amazon and Azure machine learning, or Google's TensorFlowDeploying and managing in Cloud Computing such ...

practice focuses on helping clients control their data, turn it into actionable insights, and better leverage it through the use of AI and Machine Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/… scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks.Machine Learning Engineering: End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge ...

practice focuses on helping clients control their data, turn it into actionable insights, and better leverage it through the use of AI and Machine Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/… scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks.Machine Learning Engineering: End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge ...

join us. About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build … recommender systems, forecasting models, and more. We're looking for an AI & ML Engineer who is passionate about building production-ready AI and machine learning solutions. You'll work across a variety of AI initiatives, contributing to the design, implementation and deployment of scalable AI systems. ...

About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions … Hands‐on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud‐native AI/ML platforms (e.g. AWS SageMaker, AzureML) and agent orchestration frameworks (e.g. LangChain, LangGraph, ADK). Solid understanding of MLOps – CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven ...

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 ...

third-party partners to deliver secure, resilient and scalable digital services . Key Responsibilities Own and improve CI/CD pipelines across Azure DevOps and GitHub. Support and optimise production environments, resolving complex incidents and problems. Drive monitoring, observability, performance and reliability improvements. Develop and maintain Infrastructure … DevOps or Azure Architecture certification. Experience with ITIL/ISO27001. Azure MLOps/operationalising machine-learning models. Experience integrating AI/agent-based solutions into enterprise environments. Experience with Akamai or similar CDN platforms. #J-18808-Ljbffr ...

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 requirements into clear, concise, and actionable technical specifications and user stories for AI and data solutionsKnowledge of how data and analytics, including machine learning and AI, can be strategically leveraged to achieve wider business goals within an industry (e.g. Financial Services, Healthcare, Government & public sector … shore development teams, ensuring alignment and timely delivery of high-quality AI and data solutionsFamiliarity with cloud data platforms providers (e.g., AWS, Azure, GCP, Snowflake, Databricks) and their data and AI services (e.g., S3, Azure Data Lake, BigQuery, Azure ML, Vertex ...

observability tools (e.g. Prometheus, Grafana, Elastic stack). Experience with Infrastructure as Code (Terraform). Experience with Azure Experience with Machine Learning Experience in building product for the construction industry. Additional InformationOur Hiring Process 25-minute screening call Take-home challenge: A hands ...