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Black Forest Labs

Product Research Lead

Black Forest Labs is hiring a Product Research Lead. Level rates it ; you can apply on Level.

AI in this role

stable-diffusion
fine-tuning

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 videos. 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

Our model research moves fast. What's missing is someone accountable for one question: what should our models get better at next, and how will we know when they have?

You’ll lead Product Research, the team between our researchers and the market. You’ll take raw signal from evals, leaderboards, customers and usage data, turn it into a clear measure of where our models stand, and decide which gaps matter most. Your squad of Applied Researchers runs the evals and closes those gaps through post-training. You’ll work closely with Research, Backend, Product and GTM.

What You'll Work On

  • Evaluations. Own the product-facing eval taxonomy, eval strategy, and eval runs.

  • Priorities. Maintain a ranked list of what our models should get better at, built from evals, leaderboards, customer feedback and usage data, and make sure it shapes every research cycle.

  • Applied post-training. Set the priorities for the squad's Applied Researchers, who finetune and run RL to improve our core models and to build variants for specific customers and products. You decide what's worth building, define what success looks like, and check that results hold up with no regressions.

  • Data. Define the data we need to measure and improve our models.

  • Model releases. Co-lead new model releases. You own the quality go/no-go and the capability claims.

What We're Looking For

  • PM experience (product or research) working directly on generative models. You've shaped the model itself rather than building features on top of it.

  • Real technical depth. You can read an eval design and spot what's wrong with it, and you understand finetuning and RL well enough to scope and challenge the work. Researchers take you seriously because of what you know.

  • Strong judgment on trade-offs made with incomplete signal, and the drive to own prioritization end to end.

  • Comfort in an ambiguous, fast-changing research environment, where the right priority shifts as the model and harness evolve.

You've done at least one of these:

  • Defined what a generative model should get better at, and got a research team to act on it.

  • Turned a messy backlog of model weaknesses into ranked priorities that survived contact with a research org. Sources might include bug reports, leaderboard gaps, and customer complaints.

  • Owned evaluation for a model release, including the ship call or the capability claims.

  • Scoped and shipped a finetuned model or variant for a specific customer or product need.

  • Diagnosed a quality regression or plateau and traced it to a data, training, or eval-design cause.

Nice to have: hands-on eval or ML engineering experience, and experience with diffusion or video models.

How We Work Together

We’re a distributed team with real offices that people actually use. You’ll join us in Freiburg at least 2 days a week (or one full week every other week). We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process.

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.

Compensation : 172K-220K base + equity, depending on profile

How we rate this

Product Research Lead at Black Forest Labs rates 90 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. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningStable Diffusion

Questions you could be asked

  1. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  2. Walk me through how you've used Stable Diffusion in your day-to-day work.
  3. How would you decide a model or AI system is ready to ship?
  4. 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: Fine-tuning and 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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