[Job Overview]:
The work in mainly focused in building of the application starting from gathering the detailed requirement and proposing a solution (tools and frameworks) for the same and building the solution. Have communication with business team on the need and progress of the project. Cross-skilling/skill upgrade is a culture that’s followed in the project.
[Primary Skills]:
• 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, Azure OpenAI, Azure Cognitive Search, Azure Functions, Azure Cosmos DB 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 accordance with 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.
[Good to have Skills]:
• Proficiency in programming languages such as Python or R, and experience with machine learning libraries/frameworks like TensorFlow, PyTorch, or scikit
• Experience with DevOps practices and CI/CD pipelines for machine learning models is a plus
• Relevant Azure certifications (such as Azure AI Engineer or Azure Data Scientist) are advantageous.
[Responsibilities and Duties]:
• Working closely with application, network, and security teams to ensure requirements are reflected appropriately in the Azure design;
• Designing, testing, and implementing application services migrations in both a manual and automated manner;
• Working closely with client operational resources in updating their on-premise practices to include cloud;
• Develop PoC as and when required;
• Provide expertise and leadership regarding solutions for infrastructure and applications in Microsoft Azure;
• Demonstrate thought leadership in cloud computing across multiple streams;
• Develops technical roadmaps for future Azure cloud implementations;
• Ensures security is integrated into all cloud architecture solutions.
• Flexibility to work on Integration products through cross-skilling
• Flexibility to work on holidays & weekends (on rotation, compensated with holidays on weekdays)
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