Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems; Maharashtra; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

EPAM Systems in Maharashtra, India, is seeking a Senior Systems Engineer specialized in Data DevOps/MLOps to join our team. You will design CI/CD pipelines, deploy cloud infrastructure, and automate ML workflows to production.

You will collaborate with data scientists and engineers to scale ML models, ensure reproducibility, and maintain security and monitoring across data pipelines. The role demands strong Python, cloud, and IaC skills.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline.
• Minimum 5 years of experience in Data DevOps, MLOps, or similar roles.
• Hands-on experience with Azure, AWS, or Google Cloud Platform.
• Experience with IaC tools such as Terraform, CloudFormation, or Ansible.
• Strong containerization and orchestration with Docker and Kubernetes.
• Experience with Spark or Databricks for data processing.
• Solid Python skills with Pandas, TensorFlow, or PyTorch.
• Familiarity with CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions.
• Understanding of Git and ML platforms like MLflow or Kubeflow.
• Familiarity with monitoring/logging/alerting tools like Prometheus or Grafana.
• Strong problem-solving, independence or team collaboration, and communication/documentation.

Responsibilities

• Design CI/CD pipelines for data integration and ML model deployment.
• Deploy and maintain cloud-based data processing and model training infrastructure.
• Automate data validation, transformation, and orchestration workflows.
• Collaborate with data scientists and engineers to productionize ML models.
• Improve performance and reliability of model serving and monitoring.
• Maintain data versioning, lineage, and reproducibility across ML experiments.
• Identify opportunities to strengthen deployment processes and infrastructure.
• Apply security protocols to protect data integrity and compliance.
• Troubleshoot issues across the data and ML pipeline lifecycle.

Skills

Data DevOps

MLOps

CI/CD pipelines

Python

Docker

Kubernetes

Spark/Databricks

Terraform

Git

Monitoring (Prometheus/Grafana)

Team collaboration

Documentation

Education

Bachelor's or Master's in Computer Science/Data Engineering

Tools

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Jenkins

GitLab CI/CD

GitHub Actions

MLflow

Kubeflow

Prometheus

Grafana

Git

Job description

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

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