EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of cutting-edge projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential._

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 strong proficiency in Python for scripting and automation
- Hands-on experience with Azure Machine Learning, Azure Databricks, and a strong 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 Compu

📌 Mlops Architect (Pune)
🏢 EPAM Systems
📍 Pune