Member of Technical Staff - VLM

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 Vision-language models are becoming foundational to how people interact with generative AI — but most VLM research happens in isolation from the generation stack. At Black Forest Labs, we're integrating VLMs directly into FLUX in ways that make our models more powerful, more controllable, and more aligned with what creators actually want. This role is about pioneering that integration. You won't be applying off-the-shelf VLMs — you'll develop novel approaches, innovate on architectures, and answer questions that haven't been solved yet: how vision and language representations inform each other, how multimodal understanding improves generation quality, and how to make these capabilities deployable at scale without compromising what makes FLUX exceptional. This is a Staff / Senior IC role. We're looking for someone who has pretrained or significantly advanced a VLM, not just fine-tuned one. WHAT YOU'LL WORK ON - Lead development and training of state-of-the-art multimodal vision-language models within the FLUX stack — innovating on architectures, not just applying existing ones - Design fine-tuning strategies that adapt VLMs to specialized creative use cases (captioning, editing instructions, prompt enhancement) that general-purpose models can't handle - Research integrations between VLM/LLM capabilities and our diffusion and flow pipelines — finding creative ways to improve generation quality and controllability without computational bottlenecks - Evaluate emerging multimodal architectures, translating the best of recent research into practical improvements WHAT WE'RE LOOKING FOR - You've pretrained or significantly advanced a VLM (not just SFT'd or LoRA'd one) that was deployed in a production system or released publicly - Strong publication record or unambiguous production track record showing you push the frontier on multimodal architectures - Deep understanding of how vision and language representations interact: tokenization, alignment, grounding, cross-modal attention, and the failure modes of each - Experience with distributed training at multi-node scale - Comfortable at the research/production boundary — you care whether the work ships and generalizes, not just whether it reads well - Experience with diffusion or flow-based generative models is a strong plus — especially if you've thought about how autoregressive and diffusion paradigms can compose HOW WE WORK TOGETHER We’re a distributed team with real offices that people actually use. This role is based in Freiburg, and you’ll join us in the office at least 2 days a week, or one full week every other week. 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 €130,000-€340,000 + Equity Note: We may use AI-assisted tools to help organize applications. All hiring decisions are always made by our team.