DevOps Cloud Engineer

Overview

DevOps Cloud Engineer
Experience: 5+ years
Work Mode: Hybrid
Location: Pune

Key Responsibilities:

• Design and maintain scalable ML model deployment infrastructure using Kubernetes and Docker.
• Implement CI/CD pipelines for ML workflows and automate deployment processes.
• Ensure security best practices are followed across all environments and data workflows.
• Set up and maintain monitoring and observability tools to track system health, model performance, and data pipeline issues.
• Build, schedule, and manage data workflows using Apache Airflow or similar orchestration tools.
• Collaborate with ML, data, and infra teams to streamline the end-to-end lifecycle of data products.
• Identify and mitigate performance bottlenecks and data reliability issues in the ML infrastructure.

Required Skills & Qualifications:

• Strong experience with Kubernetes and Docker for containerization and orchestration.
• Hands-on experience in ML model deployment in production environments.
• Proficiency with Airflow, Luigi, or other orchestration tools.
• Familiarity with monitoring tools like Prometheus, Grafana, ELK Stack, or similar.
• Knowledge of security protocols, identity access management, and role-based access control.
• Experience in CI/CD pipelines and DevOps practices in a data/ML environment.
• Understanding of data pipelines and streaming frameworks is a plus.
• Exposure to cloud platforms (AWS/GCP/Azure) is preferred.

Nice to Have:

• Experience with MLflow, Seldon, or Kubeflow.
• Knowledge of data governance, lineage, and compliance standards.

Job Type: Full-time

Pay: ₹2,500,000.00 per year

Experience:

• MLops: 5 years (Required)

Work Location: In person