We are seeking a highly skilled MLOps Architect to join our team and lead the design and implementation of robust and scalable MLOps solutions on the Azure cloud platform. The ideal candidate will have a solid background in cloud-based machine learning operations, DevOps practices, and data engineering, with a focus on unstructured data in industries such as automotive.

Responsibilities Design and maintain scalable MLOps infrastructure within the Azure ecosystem

Develop and optimize CI/CD pipelines for machine learning model deployment and integration

Utilize Docker for containerization and orchestrate containers with Kubernetes

Implement and manage complex data pipelines for processing large-scale unstructured data

Collaborate with data scientists and data engineers to streamline model lifecycle processes

Leverage Azure ML services such as Azure Databricks and Azure ML Workspace for end-to-end workflows

Ensure reliability, scalability,



and performance of machine learning systems in production environments Requirements 12 to 16 years of overall experience, with robust proficiency in Python for scripting and automation

Hands-on experience with Azure Machine Learning, Azure Databricks, and a solid understanding of Azure cloud services

Practical expertise in Docker, CI/CD pipelines using tools like Azure DevOps, and Kubernetes orchestration

Proven ability to design and manage complex data pipelines, particularly for unstructured data

Azure certifications (e.g., Azure Data Engineer, AI Engineer, or DevOps Engineer)

Competency with Infrastructure as Code tools like Terraform or ARM templates

Understanding of monitoring and logging tools for ML models, such as Prometheus, Grafana, or Azure Monitor

Advanced degree in Computer Science, Engineering, Data Science, or a related field is preferred

📌 Mlops Architect Pune
🏢 EPAM Systems
📍 Pune