Lead Systems Engineer - Data DevOps/MLOps

EPAM Systems India Pvt Ltd; India; Remote; INR 4,000,000 - 7,000,000; Full time

Job summary

EPAM Systems India Pvt Ltd offers an exciting Lead Systems Engineer role focused on Data DevOps and MLOps across multiple Indian offices. You will design and deploy end-to-end CI/CD pipelines for data and ML workflows, build scalable cloud infrastructure, and work with data scientists to productionize models.

The ideal candidate has 8+ years in Data DevOps/MLOps, strong cloud and IaC skills, and hands-on experience with Spark, Databricks, and ML frameworks.

Qualifications

• 8+ years of experience in Data DevOps, MLOps, or related disciplines.
• Expertise in cloud platforms such as Azure, AWS, or GCP.
• Proficiency with IaC tools like Terraform, CloudFormation, or Ansible.
• Solid experience with Docker, Kubernetes for containerization and orchestration.
• Hands-on data processing with Spark and Databricks.
• Proficiency in Python with ML libraries (Pandas, TensorFlow, PyTorch).
• Familiarity with CI/CD tools (Jenkins, GitLab CI, GitHub Actions).
• Experience with ML platforms (MLflow, Kubeflow) and version control.

Responsibilities

• Design, deploy, and manage CI/CD pipelines for data integration and ML deployment.
• Build robust infrastructure for data processing, training, and serving ML models on cloud.
• Automate data validation, transformation, and orchestration workflows.
• Collaborate with data scientists and engineers to productionize ML solutions.
• Improve model serving performance, monitoring, and reliability in production.

Skills

Data DevOps

MLOps

CI/CD

Python

Problem solving

Education

Bachelor's or Master's in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

CloudFormation

Ansible

Databricks

Apache Spark

MLflow

Kubeflow

Job description

EPAM India>Jobs>Lead Systems Engineer - Data DevOps/MLOpsGo to search# Lead Systems Engineer - Data DevOps/MLOpsOffice in Coimbatore, Bangalore, Hyderabad, Chennai, Pune, GurgaonData DevOps& othersLead Systems Engineer - Data DevOps/MLOpsLead Systems Engineer - Data DevOps/MLOpsLead Systems Engineer - Data DevOps/MLOpsWe are seeking a skilled and passionate **Lead Systems Engineer** with Data DevOps/MLOps expertise to drive innovation and efficiency across our data and machine learning operations.Responsibilities* Design, deploy, and manage CI/CD pipelines for seamless data integration and ML model deployment* Establish robust infrastructure for processing, training, and serving machine learning models using cloud-based solutions* Automate critical workflows such as data validation, transformation, and orchestration for streamlined operations* Collaborate with cross-functional teams, including data scientists and engineers, to integrate ML solutions into production environments* Improve model serving, performance monitoring, and reliability in production ecosystems* Ensure data versioning, lineage tracking, and reproducibility across ML experiments and workflows* Identify and implement opportunities to improve scalability, efficiency, and resilience of the infrastructure* Enforce rigorous security measures to safeguard data and ensure compliance with relevant regulations* Debug and resolve technical issues in data pipelines and ML deployment workflowsRequirements* Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field* 8+ years of experience in Data DevOps, MLOps, or related disciplines* Expertise in cloud platforms such as Azure, AWS, or GCP* Skills in Infrastructure as Code tools like Terraform, CloudFormation, or Ansible* Proficiency in containerization and orchestration technologies such as Docker and Kubernetes* Hands-on experience with data processing frameworks including Apache Spark and Databricks* Proficiency in Python with familiarity with libraries including Pandas, TensorFlow, and PyTorch* Knowledge of CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions* Experience with version control systems and MLOps platforms including Git, MLflow, and Kubeflow* Understanding of monitoring and alerting tools like Prometheus and Grafana* Strong problem-solving and independent decision-making capabilities* Effective communication and technical documentation skillsNice to have* Background in DataOps methodologies and tools such as Airflow or dbt* Knowledge of data governance platforms like Collibra* Familiarity with Big Data technologies such as Hadoop or Hive* Showcase of certifications in cloud platforms or data engineering tools