Description

Key Responsibilities
Design, deploy, and operate scalable Kubernetes platforms supporting AI and machine learning workloads.
Manage and optimize batch scheduling frameworks such as Volcano and Kueue for efficient GPU resource utilization.
Lead infrastructure modernization and migration initiatives across cloud-native environments.
Develop platform automation, deployment pipelines, and infrastructure tooling using Infrastructure-as-Code practices.
Build and maintain scalable observability frameworks for Kubernetes and GPU-based workloads.
Collaborate with machine learning, platform, and engineering teams to improve workload performance and reliability.
Drive operational excellence through monitoring, performance tuning, capacity planning, and incident response.
Establish best practices for Kubernetes operations, platform security, and infrastructure governance.

Required Qualifications
Strong hands-on experience with Kubernetes and batch scheduling frameworks such as Volcano, Kueue, or similar technologies.
Solid understanding of distributed systems, containerization, and cloud-native architectures.
Experience managing large-scale workloads on Kubernetes platforms, preferably AWS EKS.
Demonstrated success leading and executing infrastructure migration projects.
Strong programming skills in Python and Golang.
Hands-on experience with Infrastructure-as-Code tools such as Terraform and Helm.
Experience implementing observability and monitoring solutions for Kubernetes and GPU clusters using tools such as Prometheus and Grafana.
Excellent troubleshooting, analytical, and problem-solving abilities.
Ability to work effectively in a fast-paced, highly collaborative engineering environment.

Preferred Qualifications
Experience supporting large-scale AI/ML training or inference platforms.
Knowledge of GPU resource management and optimization.
Experience with cloud platforms such as AWS, Azure, or GCP.
Familiarity with MLOps and machine learning infrastructure ecosystems

Key Skills

Education

Bachelor's degree