Azure MLOps Architect

Azure MLOps Architect needs 8+ years extensive experience with Azure Machine Learning (ML) and MLOps processes, including creating and optimizing ML workflows, building serving platforms, and deploying models.
Azure MLOps Architect requires:
-Azure MLOps Expertise: Extensive experience with Azure Machine Learning (ML) and MLOps processes, including creating and optimizing ML workflows, building serving platforms, and deploying models.
-ML Deployment Pipelines: Expertise in building and maintaining ML deployment pipelines in Azure, ensuring seamless model delivery to production.
-Model Experimentation: Strong background in ML model experimentation to optimize and evaluate models effectively.
-High-Performance Model Serving: In-depth experience in serving high-performance models at scale with low latency.
-MLOps Engineering & Architecture: Solid experience in MLOps engineering and designing architecture for scalable ML solutions.
Nice-to-Have Skills:
-Databricks: Experience with Databricks for data engineering and machine learning workflows.
-GCP Experience: Experience working with Google Cloud Platform (GCP) in MLOps or data engineering capacities.
-Cosmos DB (DogDB/Stardog): Knowledge of Cosmos DB, particularly with DogDB/Stardog schema, vector search, and embeddings.
-Serverless Compute & Kubernetes (AKS): Familiarity with serverless compute, Kubernetes (AKS), and containerized environments.
-Infrastructure Tools: Experience with Terraform for infrastructure as code, particularly for app development and infrastructure deployment.
-Event Hubs & API Gateways: Proficiency in designing and optimizing low-latency services, API gateways, and event hubs.
-Performance Tuning: Strong focus on performance tuning and load management for high-performance

Azure MLOps Architect duties:
-Support the development and deployment of the Azure MLOps platform to enhance PayPal's machine learning capabilities and infrastructure.
Employment Type: Full-Time
Salary: $ 75.00 Per Hour