Phoenix - Your AI AssistantAI Model Deployment — REST API, Docker & Cloud Hosting Setup
Delivery in
5 days
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What you get with this Offer
I will take your trained machine learning or deep learning model and deploy it as a scalable, production-ready REST API — covering API development with FastAPI or Flask, model serialisation and loading optimisation, Docker containerisation, cloud deployment to AWS (SageMaker, ECS, or EC2), GCP (Vertex AI or Cloud Run), or Azure (AML or Container Apps), auto-scaling configuration, health check endpoints, and basic monitoring setup. A model that lives in a Jupyter notebook or a researcher's laptop delivers zero business value; deployment is where AI investment becomes AI return.
The service includes inference API with input validation and error handling, Dockerfile and docker-compose configuration, CI/CD pipeline integration (GitHub Actions or equivalent) for model version updates, environment variable management for API keys and secrets, and a load test to validate the endpoint under expected request volumes. Documentation covering API endpoints, request/response schemas, and deployment runbook is included.
This service is designed for data science teams or businesses that have a working model and need it shipped to production reliably — without the DevOps expertise gap that keeps most ML models permanently in development.
The service includes inference API with input validation and error handling, Dockerfile and docker-compose configuration, CI/CD pipeline integration (GitHub Actions or equivalent) for model version updates, environment variable management for API keys and secrets, and a load test to validate the endpoint under expected request volumes. Documentation covering API endpoints, request/response schemas, and deployment runbook is included.
This service is designed for data science teams or businesses that have a working model and need it shipped to production reliably — without the DevOps expertise gap that keeps most ML models permanently in development.
What the Freelancer needs to start the work
Please share your trained model file (pickle, joblib, PyTorch, TensorFlow SavedModel, or ONNX), your inference code or notebook, preferred cloud provider and account access, expected request volume and latency requirements, and any existing CI/CD infrastructure I should integrate with.