You will get Custom Recommendation System | Machine learning developer | ML/AI | Python
Top Rated
Project details
AI-Powered Recommendation System:
This project involved the end-to-end development of a Machine Learning-driven Recommendation System designed to deliver hyper-personalized experiences tailored to specific business objectives. With 7+ years of experience in AI/ML, I led the design, training, and deployment of advanced recommender engines that improved customer engagement, operational efficiency, and measurable ROI.
The system architecture incorporated a range of modern approaches—including Large Language Models (LLMs), neural networks, and reinforcement learning algorithms—to adapt to complex user behavior patterns. My responsibilities spanned from data preprocessing and exploratory analysis to model training, fine-tuning, and production-grade deployment.
The solution has been successfully implemented across fintech, retail, and iGaming industries, where it significantly optimized the user journey, enhanced conversions, and improved long-term customer retention. Using generative AI, transformer-based models, and industry-best frameworks, I delivered a scalable and high-performing system designed to evolve with growing data and user needs.
This project involved the end-to-end development of a Machine Learning-driven Recommendation System designed to deliver hyper-personalized experiences tailored to specific business objectives. With 7+ years of experience in AI/ML, I led the design, training, and deployment of advanced recommender engines that improved customer engagement, operational efficiency, and measurable ROI.
The system architecture incorporated a range of modern approaches—including Large Language Models (LLMs), neural networks, and reinforcement learning algorithms—to adapt to complex user behavior patterns. My responsibilities spanned from data preprocessing and exploratory analysis to model training, fine-tuning, and production-grade deployment.
The solution has been successfully implemented across fintech, retail, and iGaming industries, where it significantly optimized the user journey, enhanced conversions, and improved long-term customer retention. Using generative AI, transformer-based models, and industry-best frameworks, I delivered a scalable and high-performing system designed to evolve with growing data and user needs.
Machine Learning Tools
Amazon SageMaker, ChatGPT, MLflow, NLTK, Open Neural Network Exchange, OpenCV, pandas, PyMC, Python, Python Scikit-Learn, PyTorch, TensorFlow, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$200
|
Standard
$6,000
|
Advanced
$30,000
|
|---|---|---|---|
| Delivery Time | 1 day | 40 days | 70 days |
Number of Revisions | 0 | 2 | 3 |
Number of Model Variations | 0 | 2 | 3 |
Number of Scenarios | 0 | 0 | 2 |
Number of Graphs/Charts | 0 | 0 | 0 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code | - |
3 reviews
(3)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
AA
Adrian A.
Mar 24, 2026
AI Agent Development
Working with Asif Chaudhary was an excellent experience! He is highly skilled in development and bug fixing, delivering top-quality work with great attention to detail. Communication was clear and timely throughout the project. I would gladly work with him again and highly recommend his services.
BJ
Bruce J.
Mar 10, 2026
Python ML Developer for NLP Clustering Prototype
OK
SI
Safdar I.
Aug 10, 2025
Fix & Deploy Advanced AI Dialogue System with n8n implementation
Asif delivered good work on the Deployment Dialogue system project His communication was top-notch, he met all deadlines despite it was very tight one, and his skills were reasonably strong. Highly Recommended.
About Asif
Generative AI Engineer | LLM, RAG, AI Automation for Business Workflow
100%
Job Success
San Francisco, United States - 3:22 pm local time
I design and build LLM-powered systems that automate business operations using RAG, AI agents, and custom backends. The goal is simple: reduce manual work, fit into how your team already operates, and build something people actually use day to day.
What I build:
AI automation systems for business workflows
AI agents for support, operations, and internal tools
RAG-based knowledge systems connected to docs, PDFs, or databases
Chatbots that can take real actions, not just answer questions
Backend systems for LLM-powered applications, including APIs and integrations
When clients usually reach out:
When repetitive manual processes are slowing things down
When internal knowledge is scattered or hard to access
When support or operations need automation
When they want to add real AI functionality into an existing product
When previous AI solutions did not work in real-world usage
How I approach projects:
I focus on building systems that work in practice, not just demos. That means designing around your actual workflows, keeping the backend clean and maintainable, and making sure everything integrates properly with your tools and data.
I also prioritize clear communication and iterative delivery. Most AI projects fail because of execution, not because the technology is lacking. My focus is making sure what we build actually works reliably once it is deployed.
Tech stack:
LLMs and AI tools include OpenAI, Claude, Gemini, and Llama
Frameworks include LangChain and LangGraph
Vector databases include Pinecone, FAISS, and Chroma
Backend development with Python, FastAPI, Flask, and Django
Infrastructure and integrations using Docker, APIs, and AWS
Recent work
AI agents built for workflow automation
RAG systems connected to company knowledge bases
NLP-based clustering and data processing systems
Fixing and deploying dialogue systems
Personalization systems and machine learning pipelines
If you are building something with AI, or trying to figure out the right way to approach it, feel free to message me with your use case. I can help you scope it properly and turn it into something that actually works.
Keywords
AI Engineer, LLM Engineer, Generative AI, AI Automation, AI Agents, Chatbot Development, RAG, Retrieval Augmented Generation, OpenAI API, Claude API, Gemini API, Llama, LangChain, LangGraph, Python, FastAPI, Backend Development, API Integration, Workflow Automation, NLP, Semantic Search, Vector Database, Pinecone, FAISS, ChromaDB, Knowledge Base Chatbot, PDF Chatbot, Embeddings, ML Pipeline, AI SaaS Development
Steps for completing your project
After purchasing the project, send requirements so Asif can start the project.
Delivery time starts when Asif receives requirements from you.
Asif works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Consultation
Discuss business needs, goals, and existing infrastructure to define the project's scope and expectations. Gather all necessary details and datasets for analysis.
Data Analysis & Preparation
Assess dataset quality, clean data, and prepare features to align with business objectives. Ensure data is ready for building a recommendation model.