MLOps & Cloud AI Deployments (AWS/GCP)Turyal Neeshat
I help businesses deploy, scale, and manage AI/ML models efficiently on AWS and GCP. Whether you need a CI/CD pipeline, containerization with Docker & Kubernetes or cloud cost optimization, I make sure a production-ready AI infrastructure that is scalable and efficient.
What's included
End-to-End AI Model Deployment
Deploy AI models on AWS SageMaker, GCP Vertex AI, Lambda, Cloud Run, and other cloud platforms for scalable inference.
MLOps Pipeline Setup
Build CI/CD pipelines using MLflow, Vertex Pipelines, SageMaker Pipelines, and Kubeflow for seamless model versioning and deployment.
Cloud Infrastructure Optimization
Implement auto-scaling, security best practices, and cost-saving strategies to optimize cloud resources efficiently.
Model Containerization & Orchestration
Use Docker, Kubernetes, Helm, and Terraform to package and deploy AI models with high availability and reliability.
API Development & Integration
Expose models through FastAPI, Flask, or gRPC for seamless integration with applications and business systems.
Monitoring & Logging
Set up Prometheus, Grafana, AWS CloudWatch, and GCP Stackdriver for real-time model performance monitoring and logging.
FAQs
I primarily work with AWS (SageMaker, Lambda, EC2, EKS) and GCP (Vertex AI, Cloud Run, GKE) but can also assist with Azure ML deployments.
Yes! I design cost-efficient and scalable cloud infrastructure to minimize expenses while maintaining high performance.
A standard AI model deployment takes 1-3 weeks, including testing, optimization, and monitoring setup.
Turyal 's other services
Starting at$80 /hr
Tags
AWS
Docker
FastAPI
Grafana
Kubernetes
AI Developer
DevOps Engineer
ML Engineer
Service provided by
Turyal Neeshat Karachi, Pakistan
- 4
- Followers
MLOps & Cloud AI Deployments (AWS/GCP)Turyal Neeshat
Starting at$80 /hr
Tags
AWS
Docker
FastAPI
Grafana
Kubernetes
AI Developer
DevOps Engineer
ML Engineer
I help businesses deploy, scale, and manage AI/ML models efficiently on AWS and GCP. Whether you need a CI/CD pipeline, containerization with Docker & Kubernetes or cloud cost optimization, I make sure a production-ready AI infrastructure that is scalable and efficient.
What's included
End-to-End AI Model Deployment
Deploy AI models on AWS SageMaker, GCP Vertex AI, Lambda, Cloud Run, and other cloud platforms for scalable inference.
MLOps Pipeline Setup
Build CI/CD pipelines using MLflow, Vertex Pipelines, SageMaker Pipelines, and Kubeflow for seamless model versioning and deployment.
Cloud Infrastructure Optimization
Implement auto-scaling, security best practices, and cost-saving strategies to optimize cloud resources efficiently.
Model Containerization & Orchestration
Use Docker, Kubernetes, Helm, and Terraform to package and deploy AI models with high availability and reliability.
API Development & Integration
Expose models through FastAPI, Flask, or gRPC for seamless integration with applications and business systems.
Monitoring & Logging
Set up Prometheus, Grafana, AWS CloudWatch, and GCP Stackdriver for real-time model performance monitoring and logging.
FAQs
I primarily work with AWS (SageMaker, Lambda, EC2, EKS) and GCP (Vertex AI, Cloud Run, GKE) but can also assist with Azure ML deployments.
Yes! I design cost-efficient and scalable cloud infrastructure to minimize expenses while maintaining high performance.
A standard AI model deployment takes 1-3 weeks, including testing, optimization, and monitoring setup.
Turyal 's other services
$80 /hr