Azure DevOps Professional

Company Profile:

Job Title: Azure DevOps
Position: Azure DevOps
Experience: 6 to 8
Category: IT Infrastructure
Main location: India, Karnataka, Bangalore
Primary Skill-AWS
Employment Type: Full Time
Qualification: Bachelors degree in Computer Science or related field or higher.
Roles and Responsibilities

Standard Series: General-purpose VMs suitable for a wide range of applications.
D-Series: High-performance VMs optimized for CPU-intensive tasks, useful for development and testing.
E-Series: Memory-optimized VMs ideal for in-memory applications, analytics, and large-scale data processing.
F-Series: Compute-optimized VMs designed for workloads that require a higher CPU-to-memory ratio.
G-Series: VMs offering a balanced mix of memory, storage, and compute resources, suitable for large databases and enterprise applications.
N-Series: GPU-optimized VMs ideal for heavy graphics rendering, video editing, and deep learning training.
Azure Machine Learning Compute Compute Instances: Managed VM instances for development and training. Compute Clusters: Managed clusters of VMs for large-scale training jobs. These clusters can scale up or down automatically based on demand.
Azure Kubernetes Service (AKS) AKS: Managed Kubernetes service that can be used to deploy, manage, and scale containerized applications, including machine learning models. AKS supports GPU-enabled nodes for ML workloads.
Azure Cognitive Services Cognitive Services: Pre-built AI models that can be integrated into applications via API calls. These services include vision, speech, language, and decision-making capabilities.
Hybrid and Edge Computing Azure Arc: Extends Azure management to any infrastructure, enabling AI workloads to run on-premises, at the edge, and across multiple clouds. Azure Stack: Brings Azure services to on-premises and edge environments, allowing for consistency in development and deployment.
Dedicated AI Appliances Azure AI Supercomputer: Specialized for large AI training jobs with high computational requirements. These are clusters with high-performance interconnects and a large number of GPUs. Azure Percept: Edge AI hardware for deploying AI models on the edge, useful for IoT and low-latency applications

Skills:

• Kubernetes
• DevOps
• Project Management

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