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Black Forest Labs

Member of Technical Staff - Research Infrastructure Engineer

Black Forest Labs is hiring a Member of Technical Staff - Research Infrastructure Engineer. It pays €100k-€230k a year and Level rates it ; you can apply on Black Forest Labs.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • Tools and skills the posting cites include Stable Diffusion.
  • Level classifies it as a lead role.
  • Level lists 14 other open roles at Black Forest Labs.

AI in this role

Stable Diffusion

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.

How we rate this

Member of Technical Staff - Research Infrastructure Engineer at Black Forest Labs rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Stable Diffusion

Questions you could be asked

  1. What's a project where you used Stable Diffusion hands-on?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Stable Diffusion. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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