About the role
Job Application for Member of Technical Staff - Large Scale Data Infrastructure at Black Forest Labs Back to jobs Member of Technical Staff - Large Scale Data Infrastructure Freiburg (Germany), San Francisco (USA) Apply About Black Forest Labs We’re
the team behind Latent Diffusion, Stable Diffusion, and FLUX—foundational technologies that changed how the world creates images and video. We’re creating the generative models that power how people make images and video—tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we’re just getting started. Headquartered in Freiburg, Germany with a growing presence in San Francisco, we’re scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity. Why This Role We're looking for infrastructure engineers who want to work at peta-to-exabyte scale. You'll build the data systems behind the largest training runs on thousands of GPUs, where fixing one bottleneck lets researchers train the next breakthrough model. What You’ll Work On Scalable data loaders for training runs across thousands of GPUs Efficient storage and retrieval systems for petabyte-scale datasets Multi-cloud object storage abstraction Execute large-scale data migrations across storage systems and providers Debug and resolve performance bottlenecks in distributed data loading Technical Focus Python, PyTorch DataLoader internals Object storage (e.g. S3, Azure Blob, GCS) Parquet for metadata Video: ffmpeg, PyAV, codec fundamentals What We’re Looking For Built and operated data pipelines at petabyte scale Optimized data loading Worked with petabyte-scale video and image datasets Written processing jobs operating on millions of files Debugged distributed system bottlenecks across large fleets of machines
Nice to have: Experience streaming dataset formats (e.g. WebDataset) Video codec internals and frame-accurate seeking Distributed systems experience Slurm and Kubernetes for job orchestration Experience with object storage performance tuning across providers