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Senior Systems Engineer - Data DevOps/MLOps

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Onsite

Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems

Senior Systems Engineer - Data DevOps/MLOps

Skills

Google Cloud PlatformBig DataData EngineeringDockerPythonpandasPyTorchTensorFlowDatabricksGitGitLabJenkinsGrafanaMachine LearningAWSdbtAnsiblePrometheusGitHubKubernetesGDPRApache AirflowHadoopComplianceTerraformAzure

13 days ago

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Important information


Contract type:

Temporary

Location:

Karnataka, India

Work mode:

Onsite

Published on:

7 October 2026

What they need


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 innovative 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.

We're seeking a motivated, detail-oriented Senior Systems Engineer specializing in Data DevOps/MLOps to join our team.

The right candidate will have in-depth knowledge of data engineering, data pipeline automation, and the integration of machine learning models into live environments. This position suits a collaborative individual skilled at creating, launching, and overseeing scalable data and ML pipelines that support strategic goals.

Responsibilities

  • Design CI/CD pipelines for data integration and machine learning model deployment
  • Deploy and maintain cloud-based infrastructure for data processing and model training
  • Automate workflows such as data validation, transformation, and orchestration
  • Collaborate with data scientists, software engineers, and product teams to bring ML models into production
  • Improve performance and reliability through optimized model serving and monitoring
  • Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments
  • Pinpoint opportunities to strengthen deployment processes, scalability, and infrastructure resilience
  • Apply security protocols to protect data integrity and ensure compliance
  • Troubleshoot and resolve issues across the data and ML pipeline lifecycle

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related discipline
  • At least 5 years of experience in Data DevOps, MLOps, or similar roles
  • Hands-on experience with cloud platforms such as Azure, AWS, or GCP
  • Working knowledge of Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible
  • Strong command of containerization and orchestration tools such as Docker and Kubernetes
  • Experience with data processing frameworks like Apache Spark or Databricks
  • Solid Python skills, including familiarity with data and ML libraries such as Pandas, TensorFlow, or PyTorch
  • Exposure to CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions
  • Understanding of version control systems like Git and MLOps platforms such as MLflow or Kubeflow
  • Familiarity with monitoring, logging, and alerting tools like Prometheus or Grafana
  • Sharp problem-solving skills with the ability to thrive independently or as part of a team
  • Strong communication and documentation abilities

Nice to have

  • Exposure to DataOps practices and tools such as Airflow or dbt
  • Awareness of data governance frameworks and tools like Collibra
  • Familiarity with Big Data technologies such as Hadoop or Hive
  • Certifications in cloud platforms or data engineering disciplines

We offer

  • Opportunity to work on technical challenges that may impact across geographies
  • Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
  • Opportunity to share your ideas on international platforms
  • Sponsored Tech Talks & Hackathons
  • Unlimited access to LinkedIn learning solutions
  • Possibility to relocate to any EPAM office for short and long-term projects
  • Focused individual development
  • Benefit package:
    • Health benefits
    • Retirement benefits
    • Paid time off
    • Flexible benefits
  • Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)

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