I will develop and deploy custom ml models for your products


About this gig
Transform your business with custom machine learning solutions that actually work in production.
I'm a Machine Learning Engineer specializing in building, deploying, and maintaining ML models that solve real business problems. Whether you need predictive analytics, recommendation systems, computer vision, LLMs, or any other ML application, I deliver production-ready solutions tailored to your needs.
My Scope of Work:
Phase 1: Data & Strategy (Basic)
- Exploratory Data Analysis (EDA) & Visualization.
- Data Cleaning & Preprocessing.
- Feasibility Study (Can AI actually solve this?).
Phase 2: Modeling (Standard)
- Feature Engineering & Selection.
- Model Training (Regression, Classification, Clustering, NLP, etc.).
- Hyperparameter Tuning for maximum accuracy.
- Model Evaluation (Confusion Matrix, ROC/AUC, RMSE).
Phase 3: Deployment (Premium)
- Wrapping the model in a REST API
- Dockerization for easy portability.
- Cloud Deployment (AWS/GCP/Heroku).
Why Choose Me?
- Full-Cycle Approach: I bridge the gap between Data Science and Software Engineering.
- Clean Code: Modular, commented, and ready for production.
- Post-Delivery Support: I ensure you know how to run the model.
Get to know Uche
ML Engineer
- FromNigeria
- Member sinceJan 2026
Languages
English, Russian
FAQ
Do I need to provide the dataset?
Yes, for the best results, you should provide your own dataset. If you don't have one, I can scrape data or use public datasets for an extra fee, but we must discuss this first.
What do you mean by "Database Integration"?
As an extra service, I will connect the model to your database (e.g., PostgreSQL, MongoDB) so it can automatically read new data or save its predictions directly to your system.
Can you help with model maintenance after delivery?
Yes! Premium package includes 1 month of support. I also offer monthly maintenance packages separately.
: Do you offer source code?
Yes! All packages include the full Python source code and instructions on how to run it.
What formats do you deliver?
Model files (.pkl, .h5, .pt), Python scripts, Jupyter notebooks, API code, documentation (PDF/MD), and deployment files (Dockerfile, requirements.txt, etc.)

