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 efficient ingestion and preprocessing pipelines for high-resol...