Black Forest Labs
Multimodal · Flux image-generation foundation models (Berlin)
Black Forest Labs currently has 8 active AI-related job listings. The listings are evenly distributed across post-training, pre-training, and data stages, each representing 25% of the open roles. Engineering is the most frequent function, with 5 roles, while Research has 3. The company is hiring for roles that frequently mention multimodal, fine-tuning, and model serving technologies. Over the last 30 days, Black Forest Labs has seen a 100% decrease in new AI roles, with 0 new listings compared to 2 in the previous 30-day period.
Black Forest Labs currently has 8 active AI-related roles in our index. The most common open titles are: Forward Deployed, Robotics Engineer, Member of Technical Staff - Image / Video Generation, Member of Technical Staff - Infrastructure Engineer, Member of Technical Staff - Model Serving / API Backend Engineer, Member of Technical Staff - Post Training. Most positions are in Engineering and Research.
Black Forest Labs's active AI hiring is concentrated in: post-training (25%), pre-training (25%), data (25%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Black Forest Labs is hiring AI talent in: United States (1 role).
Job postings at Black Forest Labs most frequently mention: Generative AI, Image Generation, Video Generation, Scalability, PyTorch.
In the past 30 days, Black Forest Labs has posted 0 new AI-related roles.
Multimodal · Flux image-generation foundation models (Berlin)
Currently tracking 8 active AI roles, down 29% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $180k–$300k (avg $240k).
| Title | Stage | AI score |
|---|---|---|
| Forward Deployed, Robotics Engineer Forward Deployed Robotics Engineer to integrate and deploy Black Forest Labs' generative models (Latent Diffusion, Stable Diffusion, FLUX, action/VLA models) with robotics and physical-AI customers. This role involves embedding with customers, shipping integrations, fine-tuning models, optimizing for latency and quality on real robots (on-prem and edge), prototyping use cases, and collaborating with research on novel techniques. Requires robotics engineering experience, customer interaction, and hands-on experience with action/VLA models and related ecosystems. | AgentPost-train | 9 |