Senior Cloud Engineer (Delhi)

Key Responsibilities: - Design and implement cloud architecture for AI/ML, LLM model deployment, monitoring, and scaling - Deploy models using Docker, Kubernetes, and CI/CD pipelines across cloud environments on Azure or GCP - Optimize AI model serving using tools like TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server, etc. - Build and manage IaC using Terraform, or CloudFormation - Implement security best practices, autoscaling, logging, monitoring (Prometheus/ Grafana/ ELK), and disaster recovery plans - Collaborate with ML engineers to produce prototypes into resilient, cloud-native services - Benchmark and tune deployments for low latency, high throughput, and cost optimization Required Qualifications: - 8+ years of experience in cloud engineering, with 4+ years focused on AI/ML deployment at scale - Solid hands-on expertise in Azure and GCP - Proficient in Docker, Kubernetes, Helm, and serverless deployment models - Solid understanding of ML frameworks (TensorFlow, PyTorch, scikit-learn) and model deployment workflows - Experience 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 scaling - Deploy models using Docker, Kubernetes, and CI/CD pipelines across cloud environments on Azure or GCP - Optimize AI model serving using tools like TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server, etc. - Build and manage IaC using Terraform, or CloudFormation - Implement security best practices, autoscaling, logging, monitoring (Prometheus/ Grafana/ ELK), and disaster recovery plans - Collaborate with ML engineers to produce prototypes into resilient, cloud-native services - Benchmark and tune deployments for low latency, high throughput, and cost optimization Required Qualifications: - 8+ years of experience in cloud engineering, with 4+ years focused on AI/ML deployment at scale - Solid hands-on expertise in Azure and GCP - Proficient in Docker, Kubernetes, Helm, and serverless deployment models - Solid understanding of ML frameworks (TensorFlow, PyTorch, scikit-learn) and model deployment workflows - Experience 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