1171+ DevOps Engineer (AI/ML) Jobs in India

This Glassdoor aggregated search page features 1,171+ active DevOps Engineer (AI/ML) job openings across India, spanning industries including IT services, fintech, e-commerce, SaaS, and healthcare technology. These roles focus on bridging traditional DevOps practices with AI/ML model lifecycle management, with core responsibilities including building and maintaining CI/CD pipelines for ML model deployment, implementing MLOps frameworks, managing cloud infrastructure for AI workloads (AWS, Azure, GCP), automating model training, testing, and deployment workflows, and ensuring the scalability, security, and reliability of production AI-powered systems. Salary ranges for listed roles vary based on experience level, location, and company size, with entry-level positions starting at ₹2 lakh per annum and senior specialized roles offering compensation upwards of ₹20 lakh per annum, as per Glassdoor's estimated compensation data. Listings include opportunities for fresh graduates, mid-level engineers, and senior DevOps/MLOps specialists, with flexible work arrangements including remote, hybrid, and on-site options available across major Indian tech hubs such as Bengaluru, Pune, Hyderabad, Chennai, and Delhi-NCR. Every listing includes verified company ratings, employee reviews, and detailed compensation insights to help candidates make informed application decisions.

• Proven experience in DevOps engineering with a focus on AI/ML model deployment, MLOps, or related use cases (entry-level roles open to fresh graduates with relevant projects/internships)
• Proficiency in major cloud platforms (AWS, Azure, GCP) and infrastructure-as-code tools (Terraform, CloudFormation, Pulumi)
• Hands-on experience building and maintaining CI/CD pipelines for ML model training, testing, and deployment using tools like Jenkins, GitLab CI, GitHub Actions, or CircleCI
• Familiarity with MLOps frameworks and tooling including MLflow, Kubeflow, Apache Airflow, TensorFlow Extended (TFX), or similar platforms
• Strong scripting and automation skills in Python, Bash, Go, or other relevant languages for streamlining AI/ML workflows
• Working knowledge of containerization (Docker) and orchestration (Kubernetes, EKS, GKE) for scalable AI workload management
• Understanding of production AI system monitoring, model drift detection, performance optimization, and security best practices
• Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent professional experience