Backed by a16z.
About the role
You will own the bridge between research breakthroughs and production systems. Turn research checkpoints into production-ready inference services
What they're looking for
- You’ve built and operated systems at meaningful scale. You understand the difference between a research prototype and a production system. You are comfortable navigating ambiguity, making tradeoffs, and improving systems under real-world constraints
- Building and operating ML inference services in production
- Designing scalable API architectures with async processing
- Optimizing GPU workloads (batching, quantization, compilation, CUDA)
- Managing distributed systems and task queues under variable load
- Implementing monitoring and observability for production ML systems
More about this role
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.
Our research team moves fast. Models improve weekly. New capabilities emerge constantly.
What slows us down is not model quality—it’s productionization.
Research checkpoints sit longer before becoming usable APIs
Inference is slower than it needs to be
APIs struggle under load
Demos don’t reflect the true potential of our models
This role removes the bottleneck between frontier research and production reality. Once hired, researchers ship faster, demos launch faster, and customers experience models at their best.
You will own the bridge between research breakthroughs...
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