We are looking for a highly skilled Cloud Engineer with strong expertise in Azure Machine Learning and Dev Ops practices to join our team.
In this role, you will design, develop, and maintain scalable cloud-based machine learning solutions and implement Dev Ops pipelines to support continuous integration and deployment (CI/CD) across AI models and cloud infrastructure.
You will work closely with data scientists, software engineers, and Dev Ops teams to streamline machine learning workflows and ensure efficient cloud operations.
Key Responsibilities: Cloud & Machine Learning: Design and manage cloud-based machine learning environments using Azure services like Azure Machine Learning Studio, Azure Databricks, and Azure Kubernetes Service (AKS).
Develop, deploy, and monitor machine learning models on Azure, ensuring scalability, security, and availability.
Collaborate with data science teams to operationalize machine learning models and optimize cloud infrastructure for AI workloads.
Cloud & Dev Ops Best Practices: Optimize cloud infrastructure for cost, performance, and security.
Ensure compliance with cloud security standards and data governance within the Azure environment.
Collaborate with cross-functional teams to implement best Dev Ops practices, improve workflows, and enhance the efficiency of AI/ML model deployment.
Troubleshoot and resolve any issues related to cloud infrastructure, Dev Ops pipelines, or machine learning deployments.
Key Qualifications: Cloud & ML Experience: Proven experience as a Cloud Engineer with expertise in Microsoft Azure.
Strong experience with Azure Machine Learning services (Azure ML Studio, Azure Databricks, AKS, etc.) and managing AI/ML workloads in the cloud.
Proficiency in Python and experience with ML libraries such as scikit-learn, Tensor Flow, and Py Torch.
Dev Ops Expertise: Deep understanding of Dev Ops practices, including experience building and managing CI/CD pipelines.
Hands-on experience with Azure Dev Ops, Git Hub Actions, or similar tools for automation.
Familiarity with containerization (Docker) and orchestration (Kubernetes) in a cloud environment.
Experience with Infrastructure as Code (Ia C) tools like Terraform or Azure Resource Manager (ARM).
Additional Skills: Strong understanding of cloud security, networking, and monitoring in Azure environments.
Knowledge of MLOps and the integration of Dev Ops practices into the machine learning lifecycle.
Excellent problem-solving and troubleshooting skills, with the ability to collaborate in a fast-paced environment.
Experience in Snowflake.
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