1,326 to 1,350 of 5,660 Azure Jobs in England

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

model training and inference. Cross-Cloud Execution: Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers (AWS, Azure, and GCP), ensuring portability, scalability, and cost efficiency. Specialized Model Development: Lead hands-on development, fine-tuning, and deployment of production-grade models … Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data ...

database schemas and queries primarily within SQL Server, ensuring high performance and data integrity. Contribute to and enhance our CI/CD pipelines using Azure DevOps or GitHub Actions, promoting efficient and reliable deployments. Write clean, maintainable, and well-tested code, adhering to best practices and contributing to code … with relational databases, particularly SQL Server, including schema design, query optimisation, and performance tuning. DevOps & Cloud Skills: Practical experience with CI/CD tools (Azure DevOps, GitHub Actions) and containerisation (Docker). Familiarity with Azure services (Functions, App Services, Storage, Key Vault, Azure SQL). Testing & Quality ...

database schemas and queries primarily within SQL Server, ensuring high performance and data integrity. Contribute to and enhance our CI/CD pipelines using Azure DevOps or GitHub Actions, promoting efficient and reliable deployments. Write clean, maintainable, and well-tested code, adhering to best practices and contributing to code … with relational databases, particularly SQL Server, including schema design, query optimisation, and performance tuning. DevOps & Cloud Skills: Practical experience with CI/CD tools (Azure DevOps, GitHub Actions) and containerisation (Docker). Familiarity with Azure services (Functions, App Services, Storage, Key Vault, Azure SQL). Testing & Quality ...

database schemas and queries primarily within SQL Server, ensuring high performance and data integrity. Contribute to and enhance our CI/CD pipelines using Azure DevOps or GitHub Actions, promoting efficient and reliable deployments. Write clean, maintainable, and well-tested code, adhering to best practices and contributing to code … with relational databases, particularly SQL Server, including schema design, query optimisation, and performance tuning. DevOps & Cloud Skills: Practical experience with CI/CD tools (Azure DevOps, GitHub Actions) and containerisation (Docker). Familiarity with Azure services (Functions, App Services, Storage, Key Vault, Azure SQL). Testing & Quality ...

uncover client challenges, showcase product capabilities, gather feedback, and influence development priorities. Model Deployment: Work closely with engineers to productionize models on cloud platforms (Azure, AWS, or GCP) using MLOps and DevSecOps best practices. Continuous Improvement: Partner with the Product Owner to monitor model performance and user feedback, refining … TensorFlow, Keras, PyTorch, or MXNet. Agile & DevSecOps: Familiarity with Agile methodologies and DevSecOps practices, including Git for version control. Cloud Platforms: Exposure to Azure, AWS, or GCP, with a strong interest in building scalable solutions. Communication Skills: Ability to translate complex data concepts for both technical and non-technical ...

uncover client challenges, showcase product capabilities, gather feedback, and influence development priorities. Model Deployment: Work closely with engineers to productionize models on cloud platforms (Azure, AWS, or GCP) using MLOps and DevSecOps best practices. Continuous Improvement: Partner with the Product Owner to monitor model performance and user feedback, refining … TensorFlow, Keras, PyTorch, or MXNet. Agile & DevSecOps: Familiarity with Agile methodologies and DevSecOps practices, including Git for version control. Cloud Platforms: Exposure to Azure, AWS, or GCP, with a strong interest in building scalable solutions. Communication Skills: Ability to translate complex data concepts for both technical and non-technical ...

infrastructure automation using DevOps practices. Strong hands-on experience with: Terraform, Ansible, or similar IaC tools CI/CD tools (e.g., Jenkins, GitLab CI, Azure DevOps) AND Cloud platforms (AWS, Azure, or GCP) Solid understanding of networking concepts (TCP/IP, DNS, routing, VPNs, firewalls). Familiarity with ...

Python preferred) Proven experience with DevOps workflows including Pipelines, Infrastructure as code and Observability Expertise in one or more of the major Cloud platforms (Azure, AWS, GCP) A Security first mindset with strong analytical and troubleshooting skills with the ability to work closely with engineers and stakeholders Benefits Competitive … offered for this role. Keywords: DevOps, DevSecOps, CI/CD, Terraform, Ansible, Docker, Kubernetes, PKI, secret management, secure SDLC, Prometheus, ELK, Grafana, AWS, Azure ...

DevOps-first mindset within delivery teams. DevOps & Tooling Proficiency (Preferred) Category Tools & Technologies CI/CD GitLab CI/CD, Jenkins, GitHub Actions, CircleCI, Azure DevOps Pipelines Infrastructure-as-Code Terraform, Ansible, AWS CloudFormation, Pulumi Cloud Platforms AWS, Azure, GCP, or private cloud (OpenStack) Containerization Docker, Podman Orchestration ...

ideally JavaScript/TypeScript) * Build and maintain microservices, APIs, and CI/CD pipelines * Work across cloud platforms such as AWS, GCP, or Azure * Collaborate with AI specialists to deliver next-generation AI solutions * Stay hands-on with code daily, even at senior level * As a Senior Applied … Engineer, AI Developer, Python Developer, Full Stack Engineer, Backend Engineer, Generative AI, LLM, LangChain, RAG, Microservices, CI/CD, GitHub Actions, AWS, GCP, Azure, Vector Databases, Data Pipelines, Applied AI, MLOps ...

with travel to the company’s Exeter office once per quarter . Travel and accommodation will be fully paid for. Tech Stack • .NET 8 • Azure (Functions, cloud-native services) • PostgreSQL • Next.js (separate frontend team handles this) • Playwright for E2E testing • Databricks + ML tooling • GitHub Copilot/AI-assisted … work on large-scale integrations with global systems and external APIs. What We’re Looking For • Strong backend engineering experience with .NET • Cloud experience (Azure, AWS or GCP) • Understanding of observability and reliable system design • Exposure to at least one additional programming language (Go, Python, Rust, Node, Java ...