Product Research Lead

About this 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.