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.

We are looking for a Data Engineer to help create large-scale datasets that power the next generation of generative models.

Role and Responsibilities:

• Develop and maintain scalable infrastructure for large-scale image and video data acquisition
• Manage and coordinate data transfers from various licensing partners
• Implement and deploy state-of-the-art ML models for data cleaning, processing, and preparation
• Implement scalable and efficient tools to visualize, cluster, and deeply understand the data
• Optimize and parallelize data processing workflows to handle billion-scale datasets efficiently
• Ensure data quality, diversity, and proper annotation (including captioning) for training readiness
• Getting training data from alternative sources such as user preferences into trainable format
• Work closely in the model development loop to update data as necessitated by the training trajectory

What we look for:

• Proficiency in Python and various file systems for data intensive manipulation and analysis
• Familiarity with cloud computing platforms (AWS, GCP, or Azure) and Slurm/HPC environments for distributed data processing
• Experience with image and video processing libraries (e.g., OpenCV, FFmpeg)
• Demonstrated ability to optimize and parallelize data processing workflows across CPUs and GPUs
• Familiarity with data annotation and captioning processes for ML training datasets
• Knowledge of machine learning techniques for data cleaning and preprocessing

Nice to have:

• Background or keen interest in developing large-scale data acquisition systems
• Experience with natural language processing for image/video captioning
• Experience with data deduplication techniques at scale
• Experience with big data processing frameworks (e.g., Apache Spark, Hadoop)
• Experience shipping a SOTA model
• Understanding of ethical considerations in data collection and usage