You will get a deployed ML model via FastAPI and Streamlit UI on AWS
Project details
Project Summary
"With 26 years of systems engineering, I bridge the gap between raw AI prototypes and production-grade software. If you have an ML model in a notebook and need a secure, scalable AWS service, I am your partner.
I specialize in MLOps: containerization, automated CI/CD pipelines, and high-performance API development. Clients choose me to transform AI prototypes into bulletproof, stable, and business-ready applications. You get a professional, documented, and optimized service designed for long-term stability and high-availability performance."
"With 26 years of systems engineering, I bridge the gap between raw AI prototypes and production-grade software. If you have an ML model in a notebook and need a secure, scalable AWS service, I am your partner.
I specialize in MLOps: containerization, automated CI/CD pipelines, and high-performance API development. Clients choose me to transform AI prototypes into bulletproof, stable, and business-ready applications. You get a professional, documented, and optimized service designed for long-term stability and high-availability performance."
Machine Learning Tools
Amazon SageMaker, NumPy, pandas, Python Scikit-Learn, scikit-learn, SQL, XGBoostWhat's included
| Service Tiers |
Starter
$150
|
Standard
$450
|
Advanced
$950
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 0 | 3 | 5 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50 - $200
Additional Revision
+$50About Sayed
Senior MLOps & Cloud Solutions Architect | Data Engineer | Systems Exp
Arish, Egypt - 6:57 pm local time
experience in enterprise systems engineering, robust network infrastructure, and high-scale data analytics.
Specialized in executing precision migrations of machine learning models from local orchestration workspaces to
highly stable, secure, and production-grade AWS Cloud environments. Proven expert in automating full-stack
development life cycles, designing optimized CI/CD pipelines, and mastering containerized microservices (Docker).
Strongly proficient in Chaos Engineering, rigorous live server stress testing, and real-time security log analysis to
build bulletproof infrastructure. Seamlessly bridges complex software engineering with core business logic across
Logistics, Cybersecurity, and EdTech domains.
Steps for completing your project
After purchasing the project, send requirements so Sayed can start the project.
Delivery time starts when Sayed receives requirements from you.
Sayed works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery
Align on model architecture, data sources, and AWS infrastructure requirements.
Containerization & API
Dockerize your model using a high-performance FastAPI service