I will containerize and deploy your machine learning model

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Shulyak Evgenei

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

Shulyak Evgenei

MLOps and DevOps Engineer, Production ML Deployment

  • FromBelarus
  • Member sinceJun 2026
  • Languages

    Russian, English
I am an MLOps and DevOps Engineer focused on bringing Machine Learning models into production environments. I specialize in infrastructure automation, Docker/Kubernetes containerization, and building robust CI/CD pipelines for AI and software applications. Whether you need to wrap a model into a production-ready FastAPI, set up experiment tracking, or optimize your server infrastructure, I build efficient, secure, and cost-optimized environments. Let's streamline your workflows and get your code running smoothly.