You will get a trained ML model with accuracy metrics and a client-ready report
Project details
I build end-to-end machine learning solutions tailored to your specific business problem, from customer churn prediction and sales forecasting to NLP and computer vision pipelines.
Using Python, scikit-learn, XGBoost, TensorFlow/Keras, and SHAP for explainability, I deliver models that not only perform well in testing but are also understandable, documented, and ready to deploy into your actual workflow.
What sets this apart: most freelance ML deliverables stop at a Jupyter notebook with an accuracy score. I go further by validating the model against real-world edge cases, explaining why it makes the predictions it does (via SHAP), and packaging everything so your team can maintain it without me.
Whether you need a single model to prove a concept or a full pipeline feeding a live system, I scope the work to match your budget and timeline, not the other way around.
Using Python, scikit-learn, XGBoost, TensorFlow/Keras, and SHAP for explainability, I deliver models that not only perform well in testing but are also understandable, documented, and ready to deploy into your actual workflow.
What sets this apart: most freelance ML deliverables stop at a Jupyter notebook with an accuracy score. I go further by validating the model against real-world edge cases, explaining why it makes the predictions it does (via SHAP), and packaging everything so your team can maintain it without me.
Whether you need a single model to prove a concept or a full pipeline feeding a live system, I scope the work to match your budget and timeline, not the other way around.
Machine Learning Tools
Azure Machine Learning, Deeplearning4j, GitHub Copilot, Google Sheets, Keras, Microsoft Power BI, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, TensorFlow, Tesseract OCR, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$350
|
Advanced
$750
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 30 days |
Number of Revisions | 1 | 3 | 5 |
Number of Model Variations | 2 | 4 | 6 |
Number of Scenarios | 2 | 5 | 10 |
Number of Graphs/Charts | 3 | 8 | 15 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $100
Additional Revision
+$10
Additional Model Variation
(+ 2 Days)
+$20
Data Source Connectivity
(+ 2 Days)
+$25
Source Code
(+ 3 Days)
+$50About Muhammad
AI/ML Engineer | RAG, LLM Apps, Automation & API Integration
Lahore, Pakistan - 7:15 pm local time
If you're stuck between "we know AI could help" and "we don't have anyone who can actually build and deploy it," that's exactly the gap I close.
I'm an AI/ML Engineer specializing in production-ready systems: LLM-powered RAG applications, automated data pipelines, and computer vision tools that plug directly into your business, not proofs-of-concept that die in a Jupyter notebook.
Where I add the most value:
✅ RAG & LLM Applications: LangChain, ChromaDB, Groq, Sentence Transformers, custom document Q&A and chat systems
✅ Automation & Backend APIs: Python, FastAPI, Flask, workflow automation (n8n), scalable REST APIs
✅ Computer Vision: YOLO, OpenCV, OCR pipelines, image classification, product photo automation
✅ Data & BI: Power BI dashboards, Pandas, SQL, ETL pipelines, predictive modeling (XGBoost, scikit-learn)
✅ Deployment: Docker, AWS/GCP, cloud-hosted, monitored, and maintained, not "it works on my machine"
Recent work shipped:
End-to-end RAG chatbot over private documents (LangChain + ChromaDB + Groq)
YOLO object detection pipeline exported PyTorch → ONNX with benchmarking
Automated product photo compositing pipeline (background removal, shadow synthesis, batch processing at scale)
Crop disease classifier 98.79% accuracy, published research
Real-time analytics dashboards (Power BI) for daily business reporting
Why clients keep me around:
I write clean, documented code, communicate clearly on timelines and blockers, and I don't disappear after handoff. I make sure what I build keeps running.
Tags / Keywords
AI Engineer, Machine Learning Engineer, LLM Application Development, RAG (Retrieval Augmented Generation), LangChain, ChromaDB, Prompt Engineering, Python Automation, FastAPI, Flask, REST API Development, Computer Vision, YOLO, OpenCV, OCR, Data Pipeline Automation, Power BI Dashboard, Predictive Modeling, XGBoost, Model Deployment Docker, AWS GCP, n8n Automation, AI Workflow Automation, Chatbot Development, Data Analysis, ETL Pipeline
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Problem Understanding
I review your dataset and define the ML problem, target variable, and success metrics with you.
Data Preprocessing & Feature Engineering
I clean the data, handle imbalance, encode variables, and engineer relevant features.