You will get a MLOps Pipeline, End-to-end ML training and deployment pipeline
Project details
An automated ML training and deployment pipeline using Amazon Web Services, Amazon SageMaker, Terraform, and CI/CD tools enables end-to-end automation of the machine learning lifecycle. Terraform provisions and manages cloud infrastructure such as compute, storage, IAM roles, and SageMaker resources in a repeatable way.
Data is ingested and processed, then SageMaker runs training jobs to build and evaluate models. CI/CD pipelines (e.g., GitHub Actions or Jenkins) automate testing, validation, and deployment steps whenever code changes are pushed. Approved models are automatically registered and deployed to production endpoints for real-time or batch inference.
The system also includes monitoring for performance, drift detection, and logging. If issues are detected, retraining can be triggered automatically. This setup ensures scalability, reliability, faster delivery, and reduced manual effort in deploying ML solutions.
Data is ingested and processed, then SageMaker runs training jobs to build and evaluate models. CI/CD pipelines (e.g., GitHub Actions or Jenkins) automate testing, validation, and deployment steps whenever code changes are pushed. Approved models are automatically registered and deployed to production endpoints for real-time or batch inference.
The system also includes monitoring for performance, drift detection, and logging. If issues are detected, retraining can be triggered automatically. This setup ensures scalability, reliability, faster delivery, and reduced manual effort in deploying ML solutions.
Machine Learning Tools
Amazon SageMaker, Apache Mahout, Azure Machine Learning, ChatGPT, Cloudera, deeplearn.js, GitHub Copilot, Google Data Studio, Google Sheets, GPT-3, OpenCV, PyTorch, SAS, SQLWhat's included $2,500
These options are included with the project scope.
$2,500
- Delivery Time 6 days
- Number of Revisions Unlimited
- Number of Model Variations 2
- Number of Scenarios 2
- Number of Graphs/Charts 0
- Model Validation/Testing
- Source Code
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Full Stack Developer
About Ammar
AI & Full-Stack Developer | SaaS MVPs, Web Apps | AWS
100%
Job Success
Gujranwala, Pakistan - 12:28 am local time
I'm an AI & Full-Stack Developer specializing in building scalable SaaS products, AI-powered applications, and modern web solutions that help businesses automate processes and grow faster. I work across the entire development lifecycle—from planning and architecture to development, deployment, and ongoing optimization.
My core tech stack includes React, Node.js, Python, AWS, PostgreSQL, MongoDB, REST APIs, Docker, and cloud-native technologies. I build clean, scalable, and production-ready applications with a strong focus on performance, security, and user experience.
I can help you with:
Full-stack web & mobile applications
AI-powered SaaS platforms and MVPs
Custom chatbots & AI assistants (OpenAI / ChatGPT integrations)
Workflow & API automation (Zapier, webhooks, internal tools)
Full-stack web apps with AI features such as semantic search, recommendations, document processing, and intelligent workflows
Custom APIs, third-party integrations, and cloud deployment on AWS
Whether you're validating a startup idea, building an MVP, or scaling an existing product, I focus on delivering reliable, maintainable solutions that are built for long-term growth.
100% Job Success Score · Top Rated Plus · 50+ Projects Delivered · 1,200+ Hours on Upwork
Clients rehire at a 78% rate because clean infrastructure built right the first time saves thousands in the long run.
My calendar fills up fast — click "Invite to Job" or send a message now with a quick overview of your infrastructure needs. I'll come back to you within a few hours with a honest assessment and a clear path forward. Let's build something that actually works.
Steps for completing your project
After purchasing the project, send requirements so Ammar can start the project.
Delivery time starts when Ammar receives requirements from you.
Ammar works on your project following the steps below.
Revisions may occur after the delivery date.
Setup CI/CD Pipeline & Infrastructure with Terraform