Job Description
Job Description
Design end-to-end machine learning solutions leveraging Azure ML services, considering factors such as scalability, performance, security, and cost efficiency.
Strong understanding of the following: Cloud native architecture principles, Modern architecture techniques
Strong understanding of machine learning principles, data preprocessing, and feature engineering.
In-depth experience architecting complex Azure public/private Cloud platform solutions (PaaS, SaaS, IaaS);
Architect cloud-based infrastructure and resources required for training deploying, and managing machine learning models using Azure resources like Azure Databricks, Azure Kubernetes Service (AKS), Azure VMs, etc.
Integrate diverse data sources and preprocess data for training and inference, using Azure Data Factory, Azure Data Lake, or other relevant Azure services.
Deploy models to production environments using Azure ML deployment technologies like Azure ML Service, Azure Functions, or AKS, and establish monitoring mechanisms for model performance, drift, and health.
Implement security measures, access controls, and data protection protocols in according to organizational policies and regulatory requirements.
Continuously optimize machine learning pipelines and models for performance, cost, and resource utilization using techniques like distributed computing and model quantization.
Excellent problem-solving and communication skills.
