End-to-end pipeline for training and deploying custom diffusion models
Developed a complete MLOps pipeline for training custom image generation models. The system handles dataset curation, preprocessing, distributed training across multiple GPUs, model versioning, and deployment. Implemented fine-tuning workflows for Stable Diffusion and custom architectures. Features include A/B testing for model performance, automated hyperparameter optimization, and production-ready API endpoints with load balancing. Successfully trained specialized models for technical illustration and architectural visualization.