FewerJobs.
All jobs

Member of Technical Staff - Large Scale Data Infrastructure

Black Forest Labs - Freiburg (Germany), San Francisco (USA)

Posted Dec 4, 2025

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
Not verified
Relocation assistance
Not verified
Childcare support
Not verified
Learning budget
Not verified
Verification
Not verified
Salary
Not verified not verified - source not recorded; timestamp not recorded

Was this benefit information wrong? Tell us.

Schedule

Shift type
Not verified
Weekend work
Not verified

Application

Cover letter
Not verified
Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff - Large Scale Data Infrastructure Freiburg (Germany), San Francisco (USA) 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

Read the full description at job-boards.greenhouse.io. FewerJobs shows a source-linked preview and links to the original posting.

Apply at job-boards.greenhouse.io

Apply link not verified; last-live date unavailable.

What verified means

Verified means a displayed claim has a recorded source field, a source URL when available, and a timestamp showing when FewerJobs checked or enriched the evidence.

Related jobs