Role Purpose

Build and operate the platform capabilities required to deploy, monitor, govern and continuously improve ML and GenAI solutions.

Key Responsibilities

- Build CI/CD and continuous-training pipelines for models, prompts and AI services.
- Automate packaging, deployment, approval, rollback, retirement and artifact versioning.
- Manage model registries, feature pipelines, environments and repositories.
- Monitor model performance, drift, latency, reliability, cost and data quality.
- Provision cloud and Kubernetes infrastructure through Infrastructure as Code and maintain runbooks and audit trails.

Required Skills
- Azure ML, MLflow and Databricks
- Azure DevOps, GitHub Actions or Jenkins
- Docker, Kubernetes, Terraform and Python
- Model registry,



feature store and secrets management
- Observability, release governance and incident support

Qualifications Bachelor's degree in Computer Science, Engineering or related field. Azure, Kubernetes or DevOps certification preferred.

Key Deliverables / Success Measures

- Explicit, approved deliverables aligned to squad objectives
- Evidence of quality, security, compliance and governance controls
- Predictable collaboration across business and technology stakeholders
- Measurable improvement in product adoption, delivery flow or operational outcomes

📌 Ai/ML Ops Engineer (Bengaluru)
🏢 SRS Infoway
📍 Bengaluru