Senior Systems Engineer - Data DevOps/MLOps

Epam Systems; Coimbatore District; On-site; INR 350,000 - 700,000; Full time

Job summary

Epam Systems is seeking a Senior Systems Engineer with a strong Data DevOps/MLOps focus to join our team in India. You will design and deploy scalable data pipelines, integrate ML models into production, and collaborate with data scientists, software engineers, and product teams to deliver robust ML-enabled solutions.

The role requires hands-on experience with cloud platforms, IaC, containerization, and modern data processing frameworks.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
• 5+ years of experience in Data DevOps, MLOps, or related professions.
• Strong cloud experience (Azure, AWS, or GCP).
• IaC experience with Terraform, CloudFormation, or Ansible.
• Proficiency with Docker and Kubernetes.
• Experience with Spark or Databricks for data processing.
• Proficient in Python and ML libraries such as TensorFlow or PyTorch.
• Familiarity with CI/CD tools (Jenkins, GitLab CI/CD, GitHub Actions).
• Git version control and MLflow/Kubeflow familiarity.
• Knowledge of monitoring (Prometheus/Grafana) and alerting.

Responsibilities

• Design CI/CD pipelines for data integration and ML model deployment.
• Deploy and maintain infrastructure for data processing and model training using cloud services.
• Automate data validation, transformation, and workflow orchestration.
• Coordinate with data scientists, software engineers, and product teams to integrate ML models into production environments.
• Enhance performance and reliability by optimizing model serving and monitoring processes.
• Ensure data versioning, lineage tracking, and reproducibility across ML experiments.
• Identify improvements for deployment processes, scalability, and infrastructure resilience.
• Implement security measures to safeguard data integrity and maintain compliance.
• Resolve issues in the data and ML pipeline lifecycle.

Skills

Data DevOps

MLOps

Data Engineering

Cloud Platforms

Terraform/Ansible

Docker/Kubernetes

Python

ML libraries (TensorFlow/PyTorch)

CI/CD

Git

Education

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

Tools

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Jenkins

GitLab CI/CD

GitHub Actions

MLflow/Kubeflow

Prometheus/Grafana

Airflow

dbt

Job description

We are looking for a detail-oriented and motivated Senior Systems Engineer with a strong focus on Data DevOps/MLOps to join our team.

The ideal candidate should possess a deep understanding of data engineering, automation of data pipelines, and integration of machine learning models into operational environments. This role is for a collaborative professional adept at building, deploying, and managing scalable data and ML pipelines aligned with strategic objectives.

Responsibilities

• Design CI/CD pipelines for data integration and machine learning model deployment
• Deploy and maintain infrastructure for data processing and model training using cloud services
• Automate processes like data validation, transformation, and workflow orchestration
• Coordinate with data scientists, software engineers, and product teams to integrate ML models into production environments
• Enhance performance and reliability by optimizing model serving and monitoring processes
• Ensure data versioning, lineage tracking, and reproducibility across ML experiments
• Identify improvements for deployment processes, scalability, and infrastructure resilienceImplement security measures to safeguard data integrity and maintain compliance
• Resolve issues in the data and ML pipeline lifecycle

Requirements

• Bachelors or Masters degree in Computer Science, Data Engineering, or a related field
• 5 or more years of experience in Data DevOps, MLOps, or related professions
• 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 tools such as Docker and Kubernetes
• Skills in using data processing frameworks like Apache Spark or Databricks
• Proficiency in Python, with familiarity with data manipulation and ML libraries such as Pandas, TensorFlow, or PyTorch
• Familiarity with CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions
• Knowledge of version control systems, such as Git, and MLOps platforms like MLflow or Kubeflow
• Understanding of monitoring, logging, and alerting systems like Prometheus or Grafana
• Strong problem-solving abilities with the capability to work both independently and collaboratively
• Effective communication and documentation skills

Nice to have

• Familiarity with DataOps practices and tools like Airflow or dbt
• Understanding of data governance frameworks and tools like CollibraKnowledge of Big Data technologies such as Hadoop or Hive
• Credentials in cloud platforms or data engineering activities