Job Description & How to Apply Below
Elevate cloud solutions as an Azure Engineer focusing on MLOps at a leading communications firm. Design and maintain platforms powered by Microsoft Azure, catering to AI-driven workloads.
In this senior role, your experience with cloud-native architectures will be crucial in building scalable infrastructure for production-grade machine learning. You'll collaborate with data teams to operationalize AI capabilities while managing the lifecycle of machine learning models. Your influence will drive automation and standards across the platform.
Key Responsibilities:
• Engineer scalable infrastructure leveraging Azure services
• Manage CI/CD processes and container orchestration
• Facilitate lifecycle management of machine learning models
• Work with cross-functional teams to operationalize ML solutions
• Develop observability strategies to ensure system reliability
Requirements:
• Strong practical experience with Microsoft Azure
• Proven expertise in MLOps and Databricks
• Deep knowledge of Kubernetes and cloud systems
• Familiarity with defining SLIs/SLOs for observability
• Experience in Dev Sec Ops practices and security models
Apply your cloud engineering skills to lead impactful MLOps initiatives in a fast-paced environment.
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