Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems; Chennai District; On-site; INR 5,000,000 - 7,500,000; Full time

Job summary

EPAM Systems in Chennai, India seeks a Senior Systems Engineer with strong Data DevOps and MLOps expertise to design, deploy, and manage extensive data and ML pipelines. You will collaborate with data scientists, software engineers, and product teams to operationalize models and maintain end-to-end pipelines.

The role requires hands-on experience with cloud platforms, container orchestration, data processing, and modern CI/CD practices. Strong communication and documentation skills are essential.

Qualifications

• Degree in Computer Science, Data Engineering, or related field.
• 5+ years experience in Data DevOps/MLOps or similar roles.
• Proficiency with cloud platforms such as Azure, AWS, or GCP.
• Experience with IaC tools (Terraform, CloudFormation, Ansible).
• Hands-on with Docker and Kubernetes for containerization and orchestration.
• Experience with data processing frameworks: Apache Spark, Databricks.
• Proficient in Python and ML libraries (Pandas, TensorFlow, PyTorch).
• Familiarity with CI/CD tools (Jenkins, GitLab CI/CD, GitHub Actions).
• Experience with ML platforms (MLflow, Kubeflow) and version control (Git).
• Strong monitoring/logging (Prometheus, Grafana).
• Excellent problem-solving, communication, and documentation skills.

Responsibilities

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

Skills

Data DevOps

MLOps

Cloud platforms

Infrastructure as Code

Docker

Kubernetes

Apache Spark

Databricks

Python + ML libraries

CI/CD tooling

MLflow / Kubeflow

Monitoring & observability

Communication & documentation

Education

Bachelor's or Master's in CS/Data Engineering

Tools

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Jenkins

GitLab CI/CD

GitHub Actions

MLflow

Kubeflow

Prometheus

Grafana

Airflow

dbt

Hadoop

Hive

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