Own model deployment and observability blueprints.

description: Own model deployment, observability, and automation blueprints that keep AI workloads resilient in production.

- Design CI/CD templates for data pipelines, model training, and inference
- Define infrastructure reference stacks spanning containers, GPUs, and edge
- Implement monitoring for drift, bias, data freshness, and SLA adherence
- Collaborate with SRE and security on access control and compliance
- Document runbooks, release gates, and rollback mechanisms

- 7+ years in DevOps/SRE with 4+ years focusing on MLOps
- Deep knowledge of Kubernetes, Argo, Terraform, and observability suites
- Experience orchestrating training pipelines on managed and self-hosted GPUs
- Familiarity with model registries, feature stores, and experiment tracking
- Robust scripting skills (Python, Go, or Bash) and automation mindset

Skills: Kubernetes, Argo, Terraform, MLOps, CI/CD, Python, GPU Orchestration, Monitoring

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 MLOps Lead (Bengaluru)
🏢 Kerdos Infrasoft
📍 Bengaluru