Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems Inc; Chennai District, Coimbatore District, Bengaluru; Híbrido; INR 1.500.000 - 3.200.000; Jornada completa

Descripción de la vacante

EPAM Systems Inc in Chennai seeks a Senior Systems Engineer specializing in Data DevOps/MLOps to design, build and operate scalable data and ML pipelines in production. You will collaborate with data scientists, software engineers, and product teams to deploy models reliably and efficiently.

Required skills include Python, Spark/Databricks, Docker, Kubernetes, and cloud platforms (Azure, AWS, GCP). Experience with Terraform/Ansible, GitHub Actions, MLflow/Kubeflow, and monitoring tools like

Formación

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline
• At least 5 years of experience working in Data DevOps, MLOps, or similar roles
• Hands-on experience with cloud platforms including Azure, AWS, or GCP
• Working knowledge of Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
• Strong command of containerization and orchestration solutions like Docker and Kubernetes
• Experience working with data processing frameworks such as Apache Spark or Databricks
• Solid Python skills, along with familiarity with ML and data libraries like Pandas, TensorFlow, or PyTorch
• Exposure to CI/CD tools such as Jenkins, GitLab CI/CD, or GitHub Actions
• Familiarity with Git and MLOps platforms including MLflow or Kubeflow
• Experience with monitoring, logging, and alerting tools like Prometheus or Grafana
• Strong analytical and problem-solving skills, with the ability to work solo or as part of a team
• Clear communication skills paired with strong documentation habits

Responsabilidades

• Build CI/CD pipelines to support data integration and ML model deployment
• Set up and manage cloud-based infrastructure for data processing and model training
• Streamline operations through automation of data validation, transformation, and workflow orchestration
• Partner with data scientists, software engineers, and product teams to bring ML models into production
• Boost reliability and performance through optimized model serving and monitoring
• Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments
• Pinpoint opportunities to strengthen deployment workflows, scalability, and infrastructure resilience
• Apply security protocols to protect data integrity and uphold compliance standards
• Troubleshoot and resolve issues throughout the data and ML pipeline lifecycle

Conocimientos

Data DevOps

MLOps

Azure

AWS

GCP

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Apache Spark

Databricks

Python

Pandas

TensorFlow

PyTorch

Jenkins

GitLab CI

GitHub Actions

MLflow

Kubeflow

Prometheus

Grafana

Educación

Bachelor's in CS/related

Master's in CS/related

Herramientas

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Azure

AWS

GCP

Databricks

Jenkins

GitHub Actions

GitLab CI

MLflow

Kubeflow

Prometheus

Grafana

Airflow

Hadoop

Hive

Descripción del empleo

We're seeking a motivated, detail-oriented Senior Systems Engineer who specializes in Data DevOps/MLOps to join our team.

The right candidate will have strong expertise in data engineering, pipeline automation, and embedding machine learning models into live operational systems. This position suits a collaborative individual skilled at creating, launching, and overseeing scalable data and ML pipelines that support organizational goals.

Responsibilities

• Build CI/CD pipelines to support data integration and ML model deployment
• Set up and manage cloud-based infrastructure for data processing and model training
• Streamline operations through automation of data validation, transformation, and workflow orchestration
• Partner with data scientists, software engineers, and product teams to bring ML models into production
• Boost reliability and performance through optimized model serving and monitoring
• Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments
• Pinpoint opportunities to strengthen deployment workflows, scalability, and infrastructure resilience
• Apply security protocols to protect data integrity and uphold compliance standards
• Troubleshoot and resolve issues throughout the data and ML pipeline lifecycle

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline
• At least 5 years of experience working in Data DevOps, MLOps, or similar roles
• Hands-on experience with cloud platforms including Azure, AWS, or GCP
• Working knowledge of Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
• Strong command of containerization and orchestration solutions like Docker and Kubernetes
• Experience working with data processing frameworks such as Apache Spark or Databricks
• Solid Python skills, along with familiarity with ML and data libraries like Pandas, TensorFlow, or PyTorch
• Exposure to CI/CD tools such as Jenkins, GitLab CI/CD, or GitHub Actions
• Familiarity with Git and MLOps platforms including MLflow or Kubeflow
• Experience with monitoring, logging, and alerting tools like Prometheus or Grafana
• Strong analytical and problem-solving skills, with the ability to work solo or as part of a team
• Clear communication skills paired with strong documentation habits

Nice to have

• Exposure to DataOps methodologies and tools such as Airflow or dbt
• Awareness of data governance frameworks and platforms like Collibra
• Familiarity with Big Data technologies including Hadoop or Hive
• Certifications related to cloud platforms or data engineering