ML Ops Engineer, Chanakya

About the role

The MLOps Engineer owns the model lifecycle across all defence and strategic sector deployments — from serving infrastructure and monitoring to evaluation pipelines and environment management. You ensure the system is always on, always accurate, and always auditable.

What you'll do

• Design and operate model serving infrastructure across on-prem and cloud deployments
• Build and maintain CI/CD pipelines for model updates, rollbacks, and evaluation-gated deployments
• Monitor model performance in production — latency, accuracy drift, throughput, failure modes — and build systems that surface issues before clients do
• Build evaluation infrastructure: harnesses, A/B testing, and model comparison tooling for field and lab use
• Manage containerised model serving in constrained, air-gapped, and edge environments

What you need

• 3–5 yrs of experience
• MLOps
• Machine learning
• Python
• LLMs
• ETL
• CI/CD
• Any graduate

Good to have

• Docker
• Kubernetes
• Prometheus
• Grafana
• Incident response
• Operational risk