We are looking for an Engineer to build the training infrastructure, data pipelines, and inference optimization systems for state-of-the-art Diffusion Transformer (DiT) models. This role focuses on scaling the fine-tuning and deployment of models like Qwen, Wan, and LTX-2.

Key Responsibilities

• Training Infrastructure: Design and maintain scalable pipelines for training and fine-tuning Diffusion Transformer models on large-scale GPU clusters.
• Model Optimization: Optimize the inference performance of Wan, LTX-2, and Qwen (Vision) using quantization, pruning, and hardware-aware tuning (e.g., TensorRT, FlashAttention).
• Data Engineering: Develop e...