ML Ops Engineer

About the role

Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.

What you'll do

• Design and build production-grade containerized environments using Kubernetes, OpenShift, and Docker to support distributed edge AI backends
• Design and maintain resilient, scalable cloud infrastructure across AWS and OpenStack tailored for high-throughput edge AI workloads
• Manage advanced GPU resource allocation, scheduling, and ML pipeline orchestration tools (e.g., Kubeflow) on Kubernetes clusters
• Establish resilient microservices architectures, ensuring platform high availability, fault tolerance, and security compliance
• Proactively own core platform infrastructure to boost operational maturity, eliminate system downtime risks, and streamline platform-wide deployment velocity

What you need

• 6–11 yrs of experience
• MLOps
• Machine learning
• AWS
• Kubernetes
• Docker
• Microservices
• B.Tech or B.E. or B.Sc or BCA