I will containerize and deploy your machine learning model


About this gig
Looking to take your Machine Learning model out of Jupyter Notebook and into production? I will containerize and deploy your ML models into high-performance, production-ready microservice APIs.
What I Offer:
FastAPI Wrapper: Turn your PyTorch, ONNX, or Scikit-Learn models into clean REST APIs with automatic Swagger documentation.
Dockerization: Build optimized multi-stage Dockerfiles and docker-compose setups for reliable cross-platform deployment.
MLOps Production Ready: Implement secure environment configurations, optimized inference pathways, and detailed code comments.
Database Integration: Seamlessly connect your pipeline to databases (PostgreSQL/Redis) for stateful applications.
Supported Frameworks: Python, PyTorch, TensorFlow, Scikit-Learn, ONNX.
Why Choose Me?
Clean, efficient, and well-documented code.
Focus on minimal container footprints and fast inference execution.
Professional communication and reliable support.
Please message me before placing an order so we can discuss your specific model architecture and requirements!
Get to know Shulyak Evgenei
MLOps and DevOps Engineer, Production ML Deployment
- FromBelarus
- Member sinceJun 2026
Languages
Russian, English
FAQ
What do I need to provide to start?
Please provide your trained model file (.pth, .onnx, .h5, etc.), a sample script showing how to run inference, and any specific dependency requirements.

