Lead Systems Engineer - Data DevOps/MLOps

EPAM · Coimbatore

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: blt7ibpiah8cl5565rd

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Collected role description

We're looking for a talented and dedicated Lead Systems Engineer with expertise in Data DevOps/MLOps 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 Create a strong infrastructure foundation for processing, training, and serving machine learning models through cloud-based platforms Streamline essential workflows including data validation, transformation, and orchestration to boost operational efficiency Partner with cross-functional teams, such as data scientists and engineers, to incorporate ML solutions into live production environments Enhance model serving capabilities, performance tracking, and reliability within production systems Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments and workflows Spot and execute opportunities to boost scalability, efficiency, and resilience within the infrastructure Implement 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 A Bachelor's or Master's degree in Computer Science, Data Engineering, or a comparable field is required At least 8 years of hands-on experience in Data DevOps, MLOps, or similar fields Strong command of cloud platforms including Azure, AWS, or GCP Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible Expertise in containerization and orchestration solutions like Docker and Kubernetes Practical experience working with data processing frameworks such as Apache Spark and Databricks Strong Python skills along with familiarity using libraries like Pandas, TensorFlow, and PyTorch Working knowledge of 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 Familiarity with monitoring and alerting solutions like Prometheus and Grafana Solid problem-solving abilities paired with the capacity to make independent decisions Strong communication skills along with the ability to produce clear technical documentation Nice to have Experience with DataOps methodologies and tools like Airflow or dbt Familiarity with data governance platforms such as Collibra Exposure to Big Data technologies including Hadoop or Hive Holds certifications in cloud platforms or data engineering tools

Collected experience requirement

8+ years