Senior Systems Engineer - Data DevOps MLOps

EPAM Systems; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

EPAM Systems is seeking a Senior Systems Engineer with extensive Data DevOps/MLOps expertise to design, deploy, and manage large-scale data and ML pipelines. The role collaborates with data scientists, software engineers, and product teams to operationalize models and ensure scalable, secure data processing.

The ideal candidate has 5+ years in Data DevOps/MLOps, strong cloud experience (Azure/AWS/GCP), and hands-on skills in CI/CD, IaC, and modern data frameworks.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 5+ years of experience in Data DevOps or similar roles.
• Proficiency in cloud platforms such as Azure, AWS, or GCP.
• Background in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible.
• Hands-on experience with data processing frameworks such as Apache Spark and Databricks.

Responsibilities

• Develop, deploy, and manage CI/CD pipelines for data integration and ML model deployment.
• Set up and sustain infrastructure for data processing and model training via cloud resources.
• Automate data validation, transformation, and workflow orchestration.
• Collaborate with data scientists, software engineers, and product teams for ML model production.
• Enhance model serving and monitoring for performance and reliability.
• Manage data versioning, lineage tracking, and experiment reproducibility.
• Search for deployment process, scalability, and infrastructure resilience improvements.
• Implement security protocols to safeguard data integrity and regulatory compliance.
• Troubleshoot data and ML pipeline lifecycle issues.

Skills

Data DevOps

MLOps

Cloud platforms

IaC

Docker

Kubernetes

Apache Spark

Databricks

Python

Pandas

TensorFlow

PyTorch

Jenkins

GitLab CI/CD

GitHub Actions

Git

MLflow

Kubeflow

Prometheus

Grafana

Communication

Documentation

Education

Bachelor’s or Master’s in CS/Data Eng

Tools

Terraform

CloudFormation

Ansible

Airflow

dbt

Collibra

Hadoop

Hive

Job description

Job Description:

We are looking for a dedicated and proficient Senior Systems Engineer with extensive Data DevOps/MLOps knowledge to enhance our team.

The ideal candidate should possess a comprehensive knowledge of data engineering, data pipeline automation, and machine learning model operationalization. The role demands a cooperative professional skilled in designing, deploying, and managing extensive data and ML pipelines in alignment with organizational objectives.

Responsibilities

• Develop, deploy, and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for data integration and machine learning model deployment
• Set up and sustain infrastructure for data processing and model training through cloud-based resources and services
• Automate processes for data validation, transformation, and workflow orchestration
• Work closely with data scientists, software engineers, and product teams for a smooth integration of ML models into production
• Enhance model serving and monitoring to boost performance and dependability
• Manage data versioning, lineage tracking, and the reproducibility of ML experiments
• Actively search for enhancements in deployment processes, scalability, and infrastructure resilience
• Implement stringent security protocols to safeguard data integrity and compliance with regulations
• Troubleshoot and solve issues throughout the data and ML pipeline lifecycle

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
• 5+ years of experience in Data DevOps, MLOps, or similar roles
• Proficiency in cloud platforms such as Azure, AWS, or GCP
• Background in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible
• Expertise in containerization and orchestration technologies including Docker and Kubernetes
• Hands-on experience with data processing frameworks such as Apache Spark and Databricks
• Proficiency in programming languages including Python with an understanding of data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
• Familiarity with CI/CD tools including Jenkins, GitLab CI/CD, and GitHub Actions
• Experience with version control tools and MLOps platforms such as Git, MLflow, and Kubeflow
• Strong understanding of monitoring, logging, and alerting systems including Prometheus and Grafana
• Excellent problem-solving abilities with capability to work independently and in teams
• Strong skills in communication and documentation

Nice to have

• Background in DataOps concepts and tools such as Airflow and dbt
• Knowledge of data governance platforms like Collibra
• Familiarity with Big Data technologies including Hadoop and Hive
• Certifications in cloud platforms or data engineering

Requirements: