At Black Forest Labs, we’re on a mission to advance the state of the art in generative deep learning for media, building powerful, creative, and open models that push what’s possible. Born from foundational research, we continuously create advanced infrastructure to transform ideas into images and videos. Our team pioneered Latent Diffusion, Stable Diffusion, and FLUX.1 – milestones in the evolution of generative AI. Today, these foundations power millions of creations worldwide, from individual artists to enterprise applications. Role and Responsibilities 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 What we look for: Experience 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