Scalable Cloud & DevOps Excellence: Accelerating Innovation & Reliability
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Cloud-Native AI Infrastructure:
Architect and deploy highly available, scalable, and cost-efficient AI and data platforms on leading cloud providers (AWS, Azure, GCP), leveraging serverless computing (Lambda, Cloud Functions), containerization (Docker, Kubernetes), and specialized ML services (SageMaker, Vertex AI).
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Automated MLOps & CI/CD Pipelines:
Implement end-to-end Machine Learning Operations (MLOps) and CI/CD pipelines (Jenkins, MLflow, Kubeflow) to automate model training, testing, deployment, and monitoring, ensuring rapid iteration and reliable delivery of AI solutions.
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Infrastructure as Code (IaC):
Utilize tools like Terraform, Puppet, and Ansible to automate infrastructure provisioning and configuration, reducing manual errors and accelerating deployment cycles.
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High-Performance Computing (HPC) Optimization: Fine-tune distributed computing frameworks like Spark on YARN/Kubernetes to maximize performance and efficiency for compute-intensive data processing and model training.
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