You will get Build and Deploy Production Ready AI ML Models with MLOps Pipeline
Project details
I build and deploy production-ready machine learning models for businesses that need real results not just a Jupyter notebook. With expertise in Python, Scikit-learn, TensorFlow, PyTorch, and cloud platforms (AWS, GCP, Azure), I handle the full ML lifecycle: data preprocessing, model training, hyperparameter tuning, REST API deployment, Docker containerization, and MLOps pipeline setup with automated monitoring and retraining.
Whether you need a predictive analytics model, an NLP classifier, a computer vision system, or a recommendation engine, I deliver clean, documented, production-grade code your team can maintain and scale.
What sets my work apart is the deployment layer. Most ML freelancers stop at a trained model. I go further setting up FastAPI endpoints, MLflow experiment tracking, CI/CD pipelines, and cloud infrastructure.
I work with startups, product teams, and enterprises across e-commerce, healthcare, finance, and SaaS. Every project includes full documentation and a handover session, so nothing is left unclear.
If you are ready to turn your data into a working, deployed AI system message me first, tell me about your dataset.
Whether you need a predictive analytics model, an NLP classifier, a computer vision system, or a recommendation engine, I deliver clean, documented, production-grade code your team can maintain and scale.
What sets my work apart is the deployment layer. Most ML freelancers stop at a trained model. I go further setting up FastAPI endpoints, MLflow experiment tracking, CI/CD pipelines, and cloud infrastructure.
I work with startups, product teams, and enterprises across e-commerce, healthcare, finance, and SaaS. Every project includes full documentation and a handover session, so nothing is left unclear.
If you are ready to turn your data into a working, deployed AI system message me first, tell me about your dataset.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Apache MXNet, BigDL, deeplearn.js, Deeplearning4j, Google AutoML, Keras, OpenCV, PyTorch, RapidMiner, SonnetAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$100
|
Standard
$250
|
Advanced
$350
|
|---|---|---|---|
| Delivery Time | 3 days | 4 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | |||
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50 - $100
Additional Revision
+$20
Monthly support/Monthly support/maintenance
(+ 2 Days)
+$199Frequently asked questions
About Kamran Ullah
AI / Machine Learning Engineer | LLM Fine-Tuning, Computer Vision, Gen
Islamabad, Pakistan - 1:51 pm local time
I help startups, research teams, and businesses develop scalable AI solutions from model training and data preprocessing to deployment APIs and cloud infrastructure. I combine strong research experience with practical engineering skills to deliver production-ready AI systems with high accuracy, efficiency, and scalability.
What I Can Help You With
✅ Fine-tuning and training LLMs (LoRA, QLoRA, PEFT)
✅ Transformer-based deep learning models
✅ Computer Vision applications
✅ Image classification, object detection, OCR, segmentation
✅ Generative AI pipelines and diffusion models
✅ Stable Diffusion, ControlNet, LoRA training
✅ Medical imaging and healthcare AI solutions
✅ NLP tasks and semantic search systems
✅ RAG pipelines and vector databases
✅ Dataset preprocessing, augmentation, and automation
✅ AI model optimization and inference acceleration
✅ PyTorch, TensorFlow, Keras development
✅ API integration and AI backend services
✅ AWS, Docker, Kubernetes, RunPod deployment
✅ End-to-end MLOps and cloud AI workflows
✅ Research-oriented AI development and experimentation
Technical Expertise:
AI / Deep Learning:
PyTorch
TensorFlow
Keras
Hugging Face Transformers
OpenCV
Diffusers
Scikit-learn
Generative AI:
Stable Diffusion
SDXL
LoRA / QLoRA
ControlNet
DreamBooth
Diffusion-based augmentation
Image generation workflows
NLP & LLMs:
LLM Fine-Tuning
RAG Systems
Semantic Similarity
Embeddings
Topic Modeling
Keyword Extraction
Vector Databases
LangChain
Computer Vision:
Classification
Segmentation
Detection
OCR
Medical Imaging
Vision Transformers (ViTs)
Image Enhancement
Deployment & MLOps:
FastAPI
REST APIs
Docker
Kubernetes
AWS
RunPod
CI/CD Pipelines
Model Serving
Why Clients Work with Me:
✔ Research + industry experience
✔ Production-ready AI solutions
✔ Clean and scalable code
✔ Strong communication and collaboration
✔ Fast learning and problem solving
✔ Focus on accuracy, optimization, and deployment
Steps for completing your project
After purchasing the project, send requirements so Kamran Ullah can start the project.
Delivery time starts when Kamran Ullah receives requirements from you.
Kamran Ullah works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review and Scoping
I review your dataset, define the ML task (classification, regression, NLP, CV), confirm feasibility, and share a clear project plan with expected accuracy benchmarks and delivery timeline.
Data Preprocessing and EDA
Clean, transform, and engineer features from your raw data. Handle missing values, outliers, encoding, and scaling. Deliver exploratory analysis report showing key patterns and model-ready dataset.