About the role
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
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