I will deploy and productionize your machine learning models
About this Gig
I help businesses take their trained machine learning models from notebooks to reliable, scalable production systems. As an AI/ML engineer with experience deploying models at Optialy and NextVR, I specialize in turning research code into production-ready services.
What I offer:
- Wrapping ML models (scikit-learn, TensorFlow, PyTorch, XGBoost) as REST APIs
- - Containerizing with Docker and deploying to AWS, GCP, or Azure
- - Setting up inference servers (vLLM, TorchServe, SageMaker, or custom FastAPI services)
- - Building CI/CD pipelines for automated testing and deployment
- - Monitoring, logging, and performance optimization for low-latency serving
- - Migrating existing models to more scalable cloud infrastructure
I focus on production reliability: proper error handling, versioning, rollback strategies, and clear documentation so your team can maintain the system after delivery.
Message me with details on your model, current setup, and target infrastructure, and I'll recommend the best deployment approach.
Domain:
Machine Learning
•
Deep Learning
Expertise:
Classification
•
Anomaly detection
•
Predictive analysis
Programming language:
Python
Technology:
TensorFlow
•
PyTorch
•
AWS SageMaker
Models & methods:
Machine Learning
•
Deep learning
My Portfolio
FAQ
Which cloud providers do you support?
I work with AWS, GCP, and Azure, and can also deploy to any Docker-compatible host or on-premise server.
