Senior Systems Engineer Data DevOps/MLOps

EPAM Systems is looking for a Senior Systems Engineer specializing in Data DevOps and MLOps to design and maintain robust pipelines for data integration and machine learning model deployment. Responsibilities Design CI/CD pipelines for data integration and ML model deployment Deploy and maintain infrastructure for data processing Automate data validation, transformation, and orchestration Coordinate with data scientists to integrate ML models into production Optimize model serving and monitoring Ensure data versioning and lineage tracking Implement security measures Required Skills 5+ years in Data DevOps, MLOps, or related roles Proficiency in Azure, AWS, or GCP Background in Terraform, CloudFormation, or Ansible Expertise in Docker and Kubernetes Skills in Apache Spark, Databricks, Python, TensorFlow, or PyTorch Familiarity with MLflow or Kubeflow Qualifications Bachelor's or Master's in Computer Science or Data Engineering Knowledge of Prometheus or Grafana Understanding of data governance and Collibra Expectations Work independently and collaboratively to resolve pipeline issues Maintain strong documentation Stay current with MLOps tools EPAM Systems is looking for a Senior Systems Engineer specializing in Data DevOps and MLOps to design and maintain robust pipelines for data integration and machine learning model deployment. Responsibilities Design CI/CD pipelines for data integration and ML model deployment Deploy and maintain infrastructure for data processing Automate data validation, transformation, and orchestration Coordinate with data scientists to integrate ML models into production Optimize model serving and monitoring Ensure data versioning and lineage tracking Implement security measures Required Skills 5+ years in Data DevOps, MLOps, or related roles Proficiency in Azure, AWS, or GCP Background in Terraform, CloudFormation, or Ansible Expertise in Docker and Kubernetes Skills in Apache Spark, Databricks, Python, TensorFlow, or PyTorch Familiarity with MLflow or Kubeflow Qualifications Bachelor's or Master's in Computer Science or Data Engineering Knowledge of Prometheus or Grafana Understanding of data governance and Collibra Expectations Work independently and collaboratively to resolve pipeline issues Maintain strong documentation Stay current with MLOps tools