This is for Govt of India National E-Governance Dept.

If you are from other than Bangalore, it is also fine. Location can be any major city, depending upon specific part of AI mission or hybrid.

Designation: MLOps Engineer

How to apply?

Go to this link. We have our internal tool to take through the flow. There is an optional but preferred AI screening (there is no AI auto rejection)

https://app.careerplan.app/#/a/ChSaAXvBcUHu?jt=MLOps%20Engineer&cpReturnUrl;=%2Fjob&job;_reference_id=TC-JOB-20260901-D3AXI2

MLOps Engineer

Designation: MLOps Engineer

Educational Qualification

 B.Tech / M.Tech in Computer Science, AI/ML, or related discipline.

 Certifications in DevOps or Cloud Infrastructure (AWS, Azure, or GCP) preferred.

 Research papers, case studies, or significant open source contributions(are preferred)

Experience

 3–6 years in operationalizing AI/ML models with proven experience in CI/CD automation.

 Prior exposure to deploying ML pipelines for NLP, computer vision, or speech systems.

 Familiarity with monitoring, model lifecycle management, and performance logging.

Key Responsibilities

1. Deploy and manage AI/ML models in development, staging, and production

environments.
1. Build and maintain automated pipelines for continuous integration and delivery





(CI/CD).
1. Implement real-time monitoring for model drift, latency, and inference

performance.
1. Collaborate with Solution Architect and MLOps Lead to standardize deployment

infrastructure.
1. Ensure reproducibility, rollback, and version control for deployed models.
2. Integrate AI services with NeGD’s standard APIs and observability frameworks.
3. Maintain deployment logs, error reports, and setting snapshots for audit

readiness.

Technical Competencies

 Infrastructure Tools: Jenkins, GitLab CI/CD, Docker, Kubernetes.

 Monitoring & Logging: Prometheus, Grafana, ELK Stack.

 ML Lifecycle Management: MLflow, Kubeflow, DVC.

 Cloud Platforms: AWS SageMaker, Azure ML Studio, GCP Vertex AI.

 Core: Python, Bash scripting, YAML/JSON configuration, Linux systems.

 CI/CD: Jenkins, GitLab CI, or GitHub Actions for automated deployments,

Terraform

 Governance: Traceability and Responsible AI compliance in deployment.

Pay: ₹500,000.00 - ₹1,500,000.00 per year

Application Question(s)

- What is your notice period / lead time to join ?
- Do you have any offer in hand?

Work Location: Hybrid remote in Bengaluru, Karnataka

📌 MLOps Engineer (Bengaluru)
🏢 Manomaya AI Systems
📍 Bengaluru