Black Forest Labs is a cutting-edge startup pioneering generative image and video models. Our team, which invented Stable Diffusion, Stable Video Diffusion, and FLUX.1, is currently seeking a strong researcher to work on model training and development. Role: Training large scale Diffusion (transformer) models for image and video Rigorously ablating design choices and communicating results & decisions with the broader team Reasoning about the speed and quality trade-offs of neural network architectures Ideal Experiences: Training large scale Diffusion models for image and video data Finetuning Diffusion models for image and video applications, such as, image and video upscalers, in and out painting models, etc. Deep understanding of how to effectively evaluating image and video generative models Strong proficiency in PyTorch, transformer models and other NN architectures. Deep understanding of training techniques such as FSDP, low precision training, and model parallelism Nice to have: Experience with writing forward and backward Triton kernels and ensuring their correctness while considering floating point errors Profiling, debugging, and optimizing single and multi-GPU operations using tools such as Nsight or stack trace viewers