Design a multi-tenant fine-tuning and LoRA serving platform

A model provider lets customers fine-tune its open-weight models on their own data through an API, then call the fine-tuned models through the same chat endpoint. Most use LoRA adapters. Design the platform: dataset validation, scheduling training jobs on shared GPUs, evaluating results before deployment, and serving thousands of fine-tuned variants on shared base-model replicas with near-base latency. Work out adapter sizes, how many fit per GPU, load times and training time.