You will get Generative AI, LLM & Machine Learning Development with Python & LangChain
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Top Rated
Project details
Build production-grade Generative AI, LLM, and Machine Learning solutions
using Python, LangChain, LangGraph, and AWS Bedrock — from model
development to intelligent automation pipelines.
With expertise across the full AI/ML stack, I deliver solutions that are
fast, accurate, and built to scale — LLMs, computer vision, or end-to-end
AI products.
What I build:
→ LLM & Generative AI — GPT/Claude/Gemini, prompt engineering, fine-tuning,
RAG pipelines, multi-agent systems (LangGraph)
→ Computer Vision — image classification, object detection, YOLO, OpenCV
→ NLP & Text AI — text classification, sentiment analysis, NER, BERT/GPT
→ ML Development — model design, training, evaluation, optimization
→ Data Science — data cleaning, EDA, feature engineering, forecasting
→ MLOps — model serving, FastAPI, Docker, AWS/GCP deployment
Deliverables by tier:
1. Starter: Single ML model — data prep, training, source code, docs
2. Standard: Full pipeline — model + API + deployment + testing
3. Advanced: End-to-end AI system — LLM/agents, MLOps, cloud deploy
Tech: Python · LangChain · LangGraph · AWS Bedrock · TensorFlow · PyTorch
· Hugging Face · OpenAI/Claude · Scikit-learn · FastAPI
using Python, LangChain, LangGraph, and AWS Bedrock — from model
development to intelligent automation pipelines.
With expertise across the full AI/ML stack, I deliver solutions that are
fast, accurate, and built to scale — LLMs, computer vision, or end-to-end
AI products.
What I build:
→ LLM & Generative AI — GPT/Claude/Gemini, prompt engineering, fine-tuning,
RAG pipelines, multi-agent systems (LangGraph)
→ Computer Vision — image classification, object detection, YOLO, OpenCV
→ NLP & Text AI — text classification, sentiment analysis, NER, BERT/GPT
→ ML Development — model design, training, evaluation, optimization
→ Data Science — data cleaning, EDA, feature engineering, forecasting
→ MLOps — model serving, FastAPI, Docker, AWS/GCP deployment
Deliverables by tier:
1. Starter: Single ML model — data prep, training, source code, docs
2. Standard: Full pipeline — model + API + deployment + testing
3. Advanced: End-to-end AI system — LLM/agents, MLOps, cloud deploy
Tech: Python · LangChain · LangGraph · AWS Bedrock · TensorFlow · PyTorch
· Hugging Face · OpenAI/Claude · Scikit-learn · FastAPI
AI Algorithms
Convolutional Neural Network, Gated Recurrent Unit, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Regression Analysis, Transformer Model, YOLOAI Applications
AI Chatbot, AI Mobile App Development, AI Text-to-Speech, AI-Generated Code, AIOps, Anomaly Detection, Automatic Speech Recognition, Conversational AI, Image Recognition, Natural Language Generation, Sentiment Analysis, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, ChatGPT, DALL-E, GPT-4, LLaMA, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,200
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | |||
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | ||
Model Documentation | - | ||
Model Monitoring | - | - | |
Model Testing & Optimization | - | - | |
Model Tuning | |||
Natural Language Processing | - | ||
NLP Tokenization | - | - | |
Pre-Training | - | - | |
Prompt Engineering | - | ||
Setup File | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$200 - $600Frequently asked questions
9 reviews
(9)
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EB
Ed B.
Jan 14, 2026
Technical Architecture & Strategy Brief for a Multi-Modal AI Platform
Muhammad demonstrated outstanding technical depth and strategic thinking on the Unbound AI Architecture project. His two-LLM design elegantly solves complex fine-tuning trade-offs, and his model selection (Qwen 3.1-14B) shows deep understanding of production requirements. The comprehensive data sourcing strategy, infrastructure planning, and deployment roadmap are all production-grade. Muhammad thinks like a senior architect, not just an implementer. Highly recommended for complex AI/ML projects. Would work with again
SM
Syed M.
Dec 20, 2025
AI Chatbot Development for Writing Assistance
"Mudassir is a true expert in their field. They understood the technical requirements immediately and executed the task with precision and attention to detail. The final result exceeded my expectations. I will definitely be hiring them again for future projects."
ES
Erik S.
Nov 10, 2025
Senior LangGraph Engineer - Agentic AI Workflows
Great developer!
SM
Syed M.
Nov 4, 2025
AI Chatbot Development for Writing Assistance
Throughout the project, Muhammad maintained clear and transparent communication, providing regular updates and seeking clarification whenever needed. This not only kept the project on track but also fostered a collaborative and efficient working relationship.
SM
Syed M.
Oct 15, 2025
AI Chatbot Development for Writing Assistance
Muhammad delivered Excellent work
About Muhammad
AI Engineer | AI Agents | RAG Chatbots | AI Automation | Generative AI
100%
Job Success
Attock City, Pakistan - 9:51 pm local time
AI systems that automate workflows, cut operational costs, and create measurable ROI.
With deep expertise in AI Agents, RAG pipelines, and full-stack SaaS platforms,
I architect and deliver solutions built on LangChain, LangGraph, OpenAI/Claude/Gemini,
AWS Bedrock, FastAPI, React/Next.js, and enterprise cloud stacks (AWS/GCP/Vercel).
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WHAT I BUILD
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→ AI Agents & Multi-Agent Systems
Autonomous agents with tool use, memory, and orchestration via LangGraph and
AutoGen — integrated into your CRMs, APIs, and internal workflows.
→ RAG Knowledge Chatbots
AI assistants grounded in your docs, databases, and knowledge base for
accurate, hallucination-free answers at scale.
→ Voice AI Pipelines
End-to-end voice agents using VAPI, Twilio, and ElevenLabs for support
automation, lead qualification, and outbound calling.
→ AI-Powered SaaS Development
Full-stack SaaS platforms with auth, billing, dashboards, and AI modules —
built in Next.js + FastAPI, ready to onboard real users from day one.
→ LLM Integration & Optimization
Fine-tuned prompts, custom retrieval pipelines, eval frameworks, and
cost/performance optimization for existing AI products.
→ Document Intelligence Pipelines
Smart PDF/data processing for summarization, extraction, legal/contract
review, and compliance automation.
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TECH STACK
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AI/LLM: LangChain, LangGraph, OpenAI (GPT-4o, o3), Claude 3.5,
Gemini 2.5, AWS Bedrock, Hugging Face, DeepSeek
Retrieval: Pinecone, Chroma, FAISS, Hybrid Search, vector embeddings, evals
Voice: VAPI, Twilio, ElevenLabs
Backend: Python, FastAPI, Node.js, REST APIs, WebSockets, Celery workers
Frontend: React, Next.js, TypeScript, Tailwind CSS
Data/Cloud: MongoDB, PostgreSQL, AWS, GCP, Vercel — CI/CD, security, scalability
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RESULTS CLIENTS CARE ABOUT
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- Chatbots handling 90%+ of routine queries → frees support teams, qualifies leads automatically
- RAG systems reducing lookup time by up to 80% → precise, verifiable answers with source citations
- AI SaaS MVPs delivered in weeks, not months → ready to onboard and charge real users
- Automations cutting manual ops costs by 30–50% → reliable AI + workflow orchestration
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HOW I WORK
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Discovery → Architecture → Delivery → Evaluation
(with strict gates for accuracy, latency, and cost at each stage)
- Business-first approach — I track KPIs like CSAT, AHT, conversion, and cost-to-serve
- Clear communication and frequent demos — you see progress at every stage
- Production-grade handover — scalable, documented, and maintainable code
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Ready to build something dependable?
Tell me your goal — support automation, lead gen, knowledge retrieval, voice AI,
or a full SaaS product — and I'll map the fastest path to measurable ROI.
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.
Preprocessing
Analysis, Cleaning and Preparation of Dataset. This may include Data Visualization and feature Extraction Techniques.
Model Development
Developing a model based on feature extraction done at preprocessing stage.