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Fiverr Pro
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USD
I will deploy your ml model with a full mlops pipeline
AI Engineer, LLM Apps, RAG, AI Agents, Web and Mobile Development
I'm Fakhar, an AI Engineer with 3+ years building real AI systems that save time and cut costs.
What I build:
✦ AI Agents that run your workflows automatically
✦ RAG Systems that answer questions from...
About this Gig
Is your ML model stuck in a notebook while your business waits? Deployment and monitoring are where most ML projects fail.
I will build a complete production ready MLOps pipeline using MLflow, Docker, AWS SageMaker, and GitHub Actions so your model serves predictions via API and retrains automatically.
What You Get
- Model containerization with Docker and FastAPI REST API for real time inference
- MLflow experiment tracking, model versioning, and model registry
- CI/CD pipeline with automated testing, validation, and zero downtime deployment
- AWS deployment on EC2, SageMaker, Lambda, or ECS
- Data versioning with DVC for full pipeline reproducibility
- Drift detection and model performance monitoring with alerts
- Automated retraining pipeline triggered by new data or performance drop
- Infrastructure as code using Terraform
Why Choose Me
- 3 years of hands on MLOps and machine learning deployment experience
- Real AWS production deployments using SageMaker and EC2
- CI/CD pipelines that redeploy automatically on every update
- Clean documented code your team can maintain and scale
Message me to discuss your ML deployment project today.
My Portfolio
FAQ
What do you need from me to get started?
I need your trained model file, the framework you used such as scikit learn, PyTorch, or TensorFlow, your preferred cloud platform, and access to your AWS account. If you have a GitHub repo ready that is a bonus but not required.
Can you deploy any type of machine learning model?
Yes. I work with classification, regression, NLP, computer vision, and deep learning models built on scikit learn, PyTorch, TensorFlow, XGBoost, and similar frameworks. If your model runs in Python, I can deploy it.
Will I be able to manage the pipeline myself after delivery?
Absolutely. I deliver clean, well documented code along with a handover guide covering your CI/CD pipeline, AWS infrastructure, and MLflow setup so your team can manage, update, and scale everything independently.
