Senior Cloud Engineer

Key Responsibilities: Design and implement cloud architecture for AI/ML, LLM model deployment, monitoring, and scalingDeploy models using Docker, Kubernetes, and CI/CD pipelines across cloud environments on Azure or GCPOptimize AI model serving using tools like TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server, etc.Build and manage IaC using Terraform, or CloudFormationImplement security best practices, autoscaling, logging, monitoring (Prometheus/ Grafana/ ELK), and disaster recovery plansCollaborate with ML engineers to produce prototypes into resilient, cloud-native servicesBenchmark and tune deployments for low latency, high throughput, and cost optimizationRequired Qualifications: 8+ years of experience in cloud engineering, with 4+ years focused on AI/ML deployment at scaleStrong hands-on expertise in Azure and GCPProficient in Docker, Kubernetes, Helm, and serverless deployment modelsSolid understanding of ML frameworks (TensorFlow, PyTorch, scikit-learn) and model deployment workflowsExperience in CI/CD tools (GitHub Actions, Jenkins, GitLab CI), scripting (Python, Bash), and API gateway management Skills: Cloud Engineering, Docker, Kubernetes, Azure, AI ML, Python Experience: 8.00-13.00 Years Key Responsibilities: Design and implement cloud architecture for AI/ML, LLM model deployment, monitoring, and scalingDeploy models using Docker, Kubernetes, and CI/CD pipelines across cloud environments on Azure or GCPOptimize AI model serving using tools like TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server, etc.Build and manage IaC using Terraform, or CloudFormationImplement security best practices, autoscaling, logging, monitoring (Prometheus/ Grafana/ ELK), and disaster recovery plansCollaborate with ML engineers to produce prototypes into resilient, cloud-native servicesBenchmark and tune deployments for low latency, high throughput, and cost optimizationRequired Qualifications: 8+ years of experience in cloud engineering, with 4+ years focused on AI/ML deployment at scaleStrong hands-on expertise in Azure and GCPProficient in Docker, Kubernetes, Helm, and serverless deployment modelsSolid understanding of ML frameworks (TensorFlow, PyTorch, scikit-learn) and model deployment workflowsExperience in CI/CD tools (GitHub Actions, Jenkins, GitLab CI), scripting (Python, Bash), and API gateway management Skills: Cloud Engineering, Docker, Kubernetes, Azure, AI ML, Python Experience: 8.00-13.00 Years