You will get a production-ready machine learning prediction API for your app
Project details
I build production-ready machine learning prediction APIs that your developers can call in real time — not notebooks, not demos, actual working systems.
Most ML freelancers deliver a Jupyter notebook and call it done. I deliver a FastAPI endpoint wrapped in Docker that your team can deploy and use the same day. I've built this exact stack in production at an industrial AI company where it cut manual work by 50+ hours per month.
What you get: a trained ML model on your dataset, a clean REST API endpoint, a Docker container ready for deployment, and documentation your developers can actually follow. Every tier includes source code.
Best for startups building AI-powered products, operations teams needing real-time predictions, and companies moving ML from prototype to production
Most ML freelancers deliver a Jupyter notebook and call it done. I deliver a FastAPI endpoint wrapped in Docker that your team can deploy and use the same day. I've built this exact stack in production at an industrial AI company where it cut manual work by 50+ hours per month.
What you get: a trained ML model on your dataset, a clean REST API endpoint, a Docker container ready for deployment, and documentation your developers can actually follow. Every tier includes source code.
Best for startups building AI-powered products, operations teams needing real-time predictions, and companies moving ML from prototype to production
Machine Learning Tools
Amazon SageMaker, MATLAB, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, R, scikit-learn, SciPy, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$100
|
Standard
$200
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 5 days | 7 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 1 |
Number of Graphs/Charts | 0 | 1 | 2 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Ikram Ullah
AI Engineer | Conversational AI | RAG & Workflow Automation
Mianwali, Pakistan - 2:29 am local time
👋 About Me
I am Ikram Ullah Khan, an Applied AI and Machine Learning Engineer with experience in production AI systems, industrial analytics, and MLOps. I build and deploy real-world machine learning solutions that automate processes, improve decision-making, and deliver measurable business impact, not just prototypes or demos.
I have worked on industrial AI systems, predictive maintenance pipelines, and automation workflows across engineering and data-driven environments, taking models from idea to deployment.
🛠️ What I Can Help You With
🔧 Production Machine Learning
• Predictive analytics and forecasting models
• Classification and regression systems
• Sensor and industrial data modeling
• Feature engineering and ML data pipelines
⚙️ MLOps and Deployment
• End-to-end ML pipelines using Prefect and CI/CD
• Dockerized ML environments
• Model deployment with FastAPI
• GitHub-based automation workflows
🤖 AI and NLP Automation
• Text classification and document processing
• GPT-powered workflows and automation
• AI-powered reporting and analytics tools
🏭 Industrial and Engineering AI
• Predictive maintenance systems
• Simulation-driven ML models
• Construction and automotive data analytics
• Process automation and digitalization
☁️ Tools and Stack
Python, Scikit-learn, TensorFlow, PyTorch, OpenCV
FastAPI, Docker, Prefect, GitHub CI/CD
SQL / NoSQL, AWS Lambda, API Gateway
🚀 Selected Work
• Built simulation-driven ML pipelines for predictive maintenance improving accuracy by 25 percent
• Automated ML workflows reducing manual effort by 50 plus hours per month
• Deployed containerized ML systems with CI/CD for production environments
• Developed AI APIs serving real-time predictions for business applications
• Designed industrial data pipelines for engineering analytics and automation
🤝 How I Work
• Clear scope and realistic timelines
• Production-focused solutions not academic demos
• Clean, scalable, maintainable code
• Transparent communication and regular updates
• Ownership from problem definition to deployment
✅ Best Fit Clients
• Startups building AI-driven products
• Companies automating operations with ML
• Teams needing production-ready AI systems
• Businesses working with sensor or engineering data
📬 Let us Build Something Practical
If you are looking for someone who can design, build, and deploy AI systems that actually work in production, send me a message. I will help you define the right technical approach for your project.
Steps for completing your project
After purchasing the project, send requirements so Ikram Ullah can start the project.
Delivery time starts when Ikram Ullah receives requirements from you.
Ikram Ullah works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Model Planning
Review your dataset, confirm prediction target, and agree on model approach before coding begins.
Model Training & Testing
Train and validate the ML model on your data, share accuracy results for your review.