Senior Systems Engineer - Data DevOps/MLOps

EPAM · Chennai

Source and collection record

Last observed by our collector: 8 October 2026 at 11:23 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: bltje34piv3mhhxdb9r

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Collected role description

Our team is seeking a skilled and committed Senior Systems Engineer with deep expertise in Data DevOps/MLOps to join our organization. The successful applicant should have thorough understanding of data engineering, automated data pipelines, and deployment of machine learning models in production. This position requires a collaborative individual capable of architecting, implementing, and overseeing large-scale data and ML pipelines that support company goals. Responsibilities Build, launch, and oversee CI/CD pipelines supporting data integration and ML model rollout Establish and maintain cloud-based infrastructure for data processing and model training Streamline data validation, transformation, and workflow orchestration through automation Partner with data scientists, software engineers, and product teams to ensure seamless ML model integration into production environments Improve model serving and monitoring capabilities to increase performance and reliability Oversee data versioning, lineage tracking, and reproducibility of ML experiments Continuously identify opportunities to improve deployment workflows, scalability, and infrastructure resilience Enforce robust security measures to protect data integrity and ensure regulatory compliance Diagnose and resolve problems across the entire data and ML pipeline lifecycle Requirements Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline Minimum 5 years of experience in Data DevOps, MLOps, or comparable positions Skilled in cloud platforms such as Azure, AWS, or GCP Experienced with Infrastructure as Code tools like Terraform, CloudFormation, or Ansible Strong knowledge of containerization and orchestration tools, including Docker and Kubernetes Practical experience with data processing frameworks such as Apache Spark and Databricks Skilled in programming languages like Python, with familiarity in data manipulation and ML libraries such as Pandas, TensorFlow, and PyTorch Knowledgeable in CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions Experienced with version control systems and MLOps platforms including Git, MLflow, and Kubeflow Solid grasp of monitoring, logging, and alerting tools such as Prometheus and Grafana Strong problem-solving skills with the ability to perform well both independently and collaboratively Excellent communication and documentation abilities Nice to have Experience with DataOps principles and tools like Airflow and dbt Understanding of data governance platforms such as Collibra Exposure to Big Data technologies including Hadoop and Hive Cloud or data engineering certifications

Collected experience requirement

5+ years