Member of Technical Staff - Large Scale Data Infrastructure

About Black Forest LabsBlack Forest Labs builds generative models for image and video used by millions of creators, developers, and businesses worldwide. Our FLUX models operate at the frontier of visual AI and are trained at scales where data movement becomes a first-order constraint.We're headquartered in Freiburg, Germany, with a growing presence in San Francisco, and we focus on research rigor, open science, and building systems that enable real breakthroughs.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 OnScalable data loaders for training runs across thousands of GPUsEfficient storage and retrieval systems for petabyte-scale datasetsMulti-cloud object storage abstractionExecute large-scale data migrations across storage systems and providersDebug and resolve performance bottlenecks in distributed data loadingTechnical FocusPython, PyTorch DataLoader internalsObject storage (e.g. S3, Azure Blob, GCS)Parquet for metadataVideo: ffmpeg, PyAV, codec fundamentalsWhat We're Looking ForBuilt and operated data pipelines at petabyte scaleOptimized data loadingWorked with petabyte-scale video and image datasetsWritten processing jobs operating on millions of filesDebugged distributed system bottlenecks across large fleets of machinesNice to have:Experience streaming dataset formats (e.g. WebDataset)Video codec internals and frame-accurate seekingDistributed systems experienceSlurm and Kubernetes for job orchestrationExperience with object storage performance tuning across providersIf this sounds like work you'd enjoy, we'd love to hear from you.Annual Salary (SF) : $180,000–$300,000 USD + Equity depending on profile and experience