You will get Deploy Your AI/ML Model to Production (FastAPI, Docker, AWS, CI/CD)
Project details
I will turn your ML model into a scalable, production-ready API with deployment, monitoring, and MLOps best practices.
Machine Learning Tools
Amazon SageMaker, ChatGPT, fastText, GitHub Copilot, Google Data Studio, Google Sheets, Kubeflow, Microsoft CNTK, Microsoft Excel, Microsoft Power BI, MLflow, NumPy, Open Neural Network Exchange, OpenCV, Python, Python Scikit-Learn, PyTorch, Salesforce Einstein, scikit-learn, SciPy, SQL, Tableau, TensorFlow, Tesseract OCR, Vertex AIWhat's included
| Service Tiers |
Starter
$100
|
Standard
$300
|
Advanced
$700
|
|---|---|---|---|
| Delivery Time | 10 days | 7 days | 4 days |
Number of Revisions | 0 | 0 | 0 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
3 reviews
(2)
(1)
(0)
(0)
(0)
This project doesn't have any reviews.
MT
Maria T.
Feb 2, 2026
Automation Developer Needed for Integration Projects
MR
Muddathir R.
Mar 5, 2025
Docker Expert Needed
Outstanding Python Developer – Highly Recommended!
Working with Naveed has been an absolute game-changer for my project. His expertise in Python is truly next level!
Working with Naveed has been an absolute game-changer for my project. His expertise in Python is truly next level!
SS
Sujagya S.
Jun 8, 2024
React Native Socket connection in a private network with a self signed certificate
About Naveed
AI Engineer & MLOps | RAG, Agents, Scalable AI Systems | Python, AWS
100%
Job Success
Lahore Cantt, Pakistan - 7:11 am local time
That gap is where I work.
✅ 𝗙𝗼𝗿𝗺𝗲𝗿 𝗔𝗜 𝗟𝗲𝗮𝗱 / Technical Leadership experience with 𝟭𝟬+ 𝘆𝗲𝗮𝗿𝘀 in AI, Machine Learning, and Backend Systems.
✅ Proven experience building production-grade AI systems, 𝗟𝗟𝗠 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀, and 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀.
✅ Strong expertise in 𝘀𝗰𝗮𝗹𝗮𝗟𝗟𝗠𝘀, 𝗥𝗔𝗚 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜, 𝗮𝗻𝗱 𝗠𝗟𝗢𝗽𝘀 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀𝗯𝗹𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀.
✅ Advanced Python development using 𝗙𝗮𝘀𝘁𝗔𝗣𝗜, 𝗙𝗹𝗮𝘀𝗸, and 𝗗𝗷𝗮𝗻𝗴𝗼 for high-performance systems
I design and build 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐫𝐞𝐚𝐝𝐲 𝐀𝐈 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 powered by 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌𝐬), machine learning, and scalable backend infrastructure. The focus is not just on building models, but on making them reliable, efficient, and usable in real business environments.
My work covers everything from 𝗟𝗟𝗠-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 and intelligent assistants to retrieval-augmented systems that connect AI with real company data. These systems are designed to handle documents, 𝘼𝙋𝙄𝙨, 𝙙𝙖𝙩𝙖𝙗𝙖𝙨𝙚𝙨, and user workflows in a way that produces accurate, context-aware outputs instead of generic responses.
A large part of my work involves building 𝗥𝗔𝗚 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, where models are combined with 𝘃𝗲𝗰𝘁𝗼𝗿 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 and 𝘀𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝘀𝗲𝗮𝗿𝗰𝗵 to deliver grounded and reliable answers. I also work on improving model performance through 𝗽𝗿𝗼𝗺𝗽𝘁 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴, evaluation, and fine-tuning techniques such as 𝗟𝗼𝗥𝗔 & 𝗤𝗟𝗼𝗥𝗔, ensuring better accuracy while controlling cost.
Beyond 𝗟𝗟𝗠𝘀, I develop 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 solutions including 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗺𝗼𝗱𝗲𝗹𝘀, recommendation systems, and 𝗡𝗟𝗣 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀. But more importantly, I make sure these models actually run in production through solid 𝗠𝗟𝗢𝗽𝘀 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 — including 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗺𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴, 𝘃𝗲𝗿𝘀𝗶𝗼𝗻𝗶𝗻𝗴, 𝗮𝗻𝗱 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘀𝘆𝘀𝘁𝗲𝗺𝘀.
On the 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝘀𝗶𝗱𝗲, I build backend systems using 𝗡𝗼𝗱𝗲𝗝𝘀,𝗙𝗮𝘀𝘁𝗔𝗣𝗜, 𝗮𝗻𝗱 𝗗𝗷𝗮𝗻𝗴𝗼, and deploy them on cloud platforms like 𝗔𝗪𝗦, 𝗚𝗖𝗣, 𝗮𝗻𝗱 𝗔𝘇𝘂𝗿𝗲. I work with 𝗗𝗼𝗰𝗸𝗲𝗿 𝗮𝗻𝗱 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 to ensure everything is scalable, maintainable, and ready for real-world usage.
𝗧𝗵𝗲 𝗴𝗼𝗮𝗹 𝗶𝘀 𝗮𝗹𝘄𝗮𝘆𝘀 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲:
To turn 𝗔𝗜 𝗶𝗱𝗲𝗮𝘀 into systems that are 𝘀𝘁𝗮𝗯𝗹𝗲, 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲, and actually useful.
𝗩𝗶𝗱𝗲𝗼 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝘁𝗶𝗼𝗻 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀:
➡️ Brainstorm and plan the initial stages of an ML project
➡️ Explain ML fundamentals in a clear, non-technical way
➡️ Discuss what AI/ML can and can’t do
➡️ Assess the feasibility of your project or idea
➡️ Provide guidance on skills to hire for, with time and cost
If you are building an 𝗔𝗜 𝗽𝗿𝗼𝗱𝘂𝗰𝘁, 𝗲𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴 𝗟𝗟𝗠 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀, or trying to move from 𝗽𝗿𝗼𝘁𝗼𝘁𝘆𝗽𝗲 𝘁𝗼 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻, I can help you design the right 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 and implement it properly.
𝐘𝐨𝐮 𝐜𝐚𝐧 𝐬𝐞𝐚𝐫𝐜𝐡 𝐦𝐞 𝐯𝐢𝐚 𝐭𝐡𝐞𝐬𝐞 𝐤𝐞𝐲𝐰𝐨𝐫𝐝𝐬:
Machine Learning Engineer, AI Developer, LLM Engineer, Generative AI Developer, MLOps Engineer, Python Developer, Backend Engineer, AI Architect, AI Consultant, Data Scientist.
Large Language Models (LLM), GPT-4, ChatGPT, OpenAI API, Claude, Gemini, LLaMA, Hugging Face Transformers.
RAG (Retrieval Augmented Generation), RAG Pipeline Development, LangChain Developer, LlamaIndex Expert, Vector Database, Pinecone, FAISS, ChromaDB, Weaviate.
AI Agents, Agentic AI, Autonomous Agents, LangGraph, AutoGPT, AI Automation, Workflow Automation, N8N, Zapier, Make.
Prompt Engineering, Prompt Optimization, LLM Fine-Tuning, LoRA, QLoRA, Model Evaluation, AI Testing.
Natural Language Processing (NLP), Text Analysis, Semantic Search, Embeddings, Document Processing, OCR AI.
Machine Learning, Deep Learning, Predictive Analytics, Classification Models, Time Series Forecasting, Recommendation Systems.
MLOps, MLflow, Weights & Biases, CI/CD for ML, Model Deployment, Model Monitoring, Data Pipelines, Feature Engineering.
FastAPI, Flask, Django, REST API Development, GraphQL, Microservices Architecture.
Docker, Kubernetes, Containerization, Scalable Systems, High-Performance APIs.
AWS (EC2, S3, Lambda, SageMaker), Google Cloud (GCP), Azure, Cloud Architecture, Serverless AI.
AI SaaS Development, Full Stack AI, React, Next.js, AI Backend Systems.
Speech AI, Whisper, Text-to-Speech (TTS), Speech-to-Text (STT), Computer Vision, Stable Diffusion.
Steps for completing your project
After purchasing the project, send requirements so Naveed can start the project.
Delivery time starts when Naveed receives requirements from you.
Naveed works on your project following the steps below.
Revisions may occur after the delivery date.
Review your model and dependencies
Wrap model into API (FastAPI)