Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

EPAM Systems is seeking a Senior Systems Engineer with deep Data DevOps/MLOps expertise to join our Hyderabad team. The role focuses on building and managing CI/CD pipelines, cloud infrastructure, data validation, and ML model deployment across production environments.

You will collaborate with data scientists, software engineers, and product teams to ensure seamless ML integration, while improving model serving, monitoring, and pipeline reproducibility.

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 comparable positions.
• Cloud platforms such as Azure, AWS, or GCP.
• Infrastructure as Code tools like Terraform, CloudFormation, or Ansible.
• Containerization and orchestration tools: Docker and Kubernetes.
• Data processing with Apache Spark and Databricks.
• Python with Pandas and ML libraries (TensorFlow, PyTorch).
• CI/CD tools: Jenkins, GitLab CI/CD, GitHub Actions.
• MLOps platforms: Git, MLflow, Kubeflow.
• Monitoring/logging: Prometheus and Grafana.
• Strong problem-solving, independent vs team capability; excellent communication.

Responsibilities

• Build, launch, and oversee CI/CD pipelines for 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 via automation.
• Collaborate with data scientists, software engineers, and product teams for ML model production.
• Improve model serving and monitoring to enhance performance and reliability.
• Oversee data versioning, lineage, and reproducibility of ML experiments.
• Identify opportunities to improve deployment workflows, scalability, and resilience.
• Enforce robust security measures to protect data and ensure regulatory compliance.
• Diagnose and resolve issues across the data and ML pipeline lifecycle.

Skills

Problem solving

Communication

Documentation

Independent & collaborative

Education

Bachelor's or Master's in CS/Data Eng/related

Tools

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Apache Spark

Databricks

Python (Pandas, ML libs)

TensorFlow

PyTorch

Jenkins

GitLab CI/CD

GitHub Actions

MLflow

Kubeflow

Prometheus

Grafana

Airflow

dbt

Collibra

Hadoop

Hive

Job description

Our team is seeking a skilled and committed Senior Systems Engineer with deep expertise in Data DevOps/MLOps to join our organization.

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