Lead Systems Engineer - Data DevOps/MLOps

EPAM · Chennai

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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: bltil3tzn4sts02w4w4

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Collected role description

We are looking for a talented and dedicated Lead Systems Engineer who brings Data DevOps/MLOps experience to enhance innovation and efficiency throughout our data and machine learning operations. Responsibilities Build, launch, and oversee CI/CD pipelines that enable smooth data integration and ML model deployment Build dependable infrastructure to support processing, training, and serving of machine learning models through cloud-based platforms Streamline key processes like data validation, transformation, and orchestration to enhance operational efficiency Partner with cross-functional teams, such as data scientists and engineers, to embed ML solutions within production systems Enhance model serving, performance tracking, and reliability within production environments Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments and workflows Discover and apply strategies to boost the scalability, efficiency, and resilience of infrastructure systems Apply strict security protocols to protect data and maintain compliance with applicable regulations Troubleshoot and fix technical problems within data pipelines and ML deployment processes Requirements Bachelor's or Master's degree in Computer Science, Data Engineering, or similar field 8+ years of professional background in Data DevOps, MLOps, or comparable areas Strong command of cloud platforms including Azure, AWS, or GCP Capability with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible Competency in containerization and orchestration solutions like Docker and Kubernetes Practical experience using data processing frameworks such as Apache Spark and Databricks Strong Python skills along with familiarity with libraries like Pandas, TensorFlow, and PyTorch Familiarity with CI/CD tools including Jenkins, GitLab CI/CD, and GitHub Actions Background using version control systems and MLOps platforms such as Git, MLflow, and Kubeflow Working knowledge of monitoring and alerting tools like Prometheus and Grafana Solid problem-solving skills paired with the ability to make independent decisions Strong communication abilities and technical documentation expertise Nice to have Experience with DataOps approaches and tools like Airflow or dbt Familiarity with data governance platforms such as Collibra Exposure to Big Data technologies including Hadoop or Hive Certifications demonstrating expertise in cloud platforms or data engineering tools

Collected experience requirement

8+ years