Lead Systems Engineer - Data DevOps/MLOps

Epam Systems; Chennai District; On-site; INR 6,000,000 - 9,000,000; Full time

Job summary

Epam Systems is seeking a Lead Systems Engineer with Data DevOps/MLOps expertise to design, deploy, and manage end-to-end data and ML pipelines in a cloud-centric environment. You will build scalable CI/CD, orchestrate data workflows, and collaborate with cross-functional teams to productionize ML models.

The role requires 8+ years in Data DevOps/MLOps, strong cloud and IaC experience, and proficiency in Python, TensorFlow, and PyTorch.

Qualifications

• 8+ years of experience in Data DevOps or MLOps.
• Proficiency with cloud platforms (Azure, AWS, GCP).
• Strong skills in DevOps tooling and CI/CD pipelines for data and ML workloads.
• Hands-on with Python data stack (Pandas, TensorFlow, PyTorch).
• Experience with version control and MLOps platforms.

Responsibilities

• Design, deploy, and manage CI/CD pipelines for data and ML deployment.
• Build scalable 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, monitoring, and reliability in production.

Skills

Data DevOps

MLOps

Python

Pandas

TensorFlow

PyTorch

CI/CD

Git

Education

Bachelor’s or Master’s in Computer Science or Data Engineering

Tools

Docker

Kubernetes

Terraform

CloudFormation

Ansible

Azure

AWS

GCP

Databricks

Apache Spark

MLflow

Kubeflow

Prometheus

Grafana

Job description

We 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 workflows

Requirements

• Bachelors or Masters 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 skills

Nice 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