Key Responsibilities:
Manage, monitor, and troubleshoot Kubernetes environments in production.
Design, implement, and maintain CI/CD pipelines using tools like Jenkins, ArgoCD, and Ansible.
Implement and maintain observability solutions (metrics, logs, traces).
Automate infrastructure and operational tasks using scripting languages such as Python, Shell, Groovy, or Ansible.
Support and optimize ML workflows, including platforms like MLflow and Kubeflow.
Collaborate with cross-functional teams to ensure infrastructure scalability, availability, and performance.
Qualifications:
Strong hands-on experience with Kubernetes and container orchestration.
Solid understanding of DevOps tools and practices.
Experience with observability platforms (e.g., Prometheus, Grafana, ELK, Datadog).
Familiarity with MLflow and Kubeflow is a strong plus.
CKS (Certified Kubernetes Security Specialist) certification is preferred.
Exposure to Big Data environments is an added advantage.
Proficient in scripting with Python, Shell, Groovy, or Ansible.
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