About the role
About Black Forest Labs
We’re the team building the foundational layer for visual intelligence: multimodal models trained jointly on images, video, audio, and action to see, generate, and understand the world.
Our founding team pioneered latent diffusion and Stable Diffusion, the breakthroughs that made generative AI accessible to millions. With FLUX, we're pushing into generative media at scale, machines that act in the physical world, and emerging applications in computer use.
Our FLUX models top public benchmarks and run in production in some of the world's biggest platforms. We're a small, fast growing research lab competing with the largest companies in the world. From our labs in Freiburg to San Francisco, we're building what comes next.
Why This Role
We're looking for engineers to build and maintain the engine that powers our mission to develop visual intelligence. From maintaining and scaling clusters, to building research platforms to accelerate the rate of innovation, this team operates with large breadth and depth. We build the systems to make multi-week/month long training possible, to orchestrate resources at scale, and at the same time efficiently, enabling the next breakthrough model. If you’re obsessed with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement, this team would be perfect for you.
What You’ll Work On
- Maintain research infrastructure, ensuring health, and optimizing components to extract peak performance from the system (both on application, and infrastructure side)
- Scale infrastructure to meet growing research demands while maintaining reliability and performance
- Collaborate with research teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency.
- Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale.
- Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets.
- Participate in on-call rotations and incident response to maintain system reliability
Technical Focus
- Python, Bash, Go
- Kubernetes
- Nvidia GPU drivers, and operators
- OTel, Prometheus
What We’re Looking For
- Experience building or operating large-scale training platforms
- Worked with large scale compute clusters (GPUs)
- Proven ability to debug performance and reliability issues across large distributed fleets
- Strong problem-solving skills and ability to work independently
- Strong communication skills and the ability to work effectively with both internal and external partners
- Deep knowledge of modern cloud infrastructure including Kubernetes, Infrastructure as Code, AWS, and GCP
- Experience with SLURM
- Experience building or operating large-scale training platforms
How We Work Together
We’re a distributed team with real offices that people actually use. You’ll be based in Europe or the US and work from your home location, with one week each month spent with us in Freiburg or San Francisco to stay connected with the team.
Everything we do is grounded in four values
- Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful.
- Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task.
- Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect.
- Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos.
If this sounds like work you’d enjoy, we’d love to hear from you.
Base Annual Salary
EU €100,000 - €230,000 + Equity
US $150,000 - $300,000 + Equity
This role is based in our Freiburg / San Francisco office. We operate a hybrid model and cover reasonable travel costs — relocation is encouraged but not required. We do expect a meaningful in-person presence, and we'll discuss what that looks like for your situation during the process.
Note: We may use AI-assisted tools to help organize applications. All hiring decisions are always made by our team.