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Tier-1 brand plus metro location but senior specialized role yields moderate candidate density.
Role requires specialized cloud, Kubernetes, MLOps platform experience, making cross-industry transferability limited.
Explicit 10+ years and many mandatory cloud, Kubernetes, IaC, and MLOps skills indicate strict filtering.
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Design, build, and maintain scalable, secure cloud infrastructure supporting AI/ML workloads, emphasizing Kubernetes and cloud-native technologies.
Develop and manage CI/CD pipelines and MLOps workflows for model deployment, training, monitoring, and validation.
Monitor platform health, ensure high availability, implement security best practices, and optimize cloud resource performance and cost.
10+ years of experience in DevOps or Cloud Platform Engineering with AI/ML infrastructure.
Strong expertise in at least one major cloud platform (AWS, Azure, or GCP) and Kubernetes container orchestration.
Proficiency with Infrastructure as Code tools like Terraform or Ansible and CI/CD tooling such as Jenkins or GitLab CI/CD.
Experience supporting AI/ML workloads in production including model deployment, MLOps frameworks, and security practices (e.g., secrets management, IAM).
Experienced in operating large-scale, secure AI/ML platforms involving Kubernetes-based containerized environments and multi-cloud or hybrid-cloud setups.
Skilled in automating infrastructure provisioning and deployment pipelines to improve reliability and efficiency for AI workloads.
Familiar with advanced AI/ML technologies such as Large Language Models, Generative AI, and GPU-based distributed training environments.