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.
Currently tracking 8 active AI roles, down 29% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $180k–$300k (avg $240k).
Multimodal · Flux image-generation foundation models (Berlin)
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.
| Title | Stage | AI score |
|---|---|---|
| Member of Technical Staff - Pretraining Research role focused on leading large-scale pretraining experiments for multimodal foundation models (image, video, audio), involving architecture, objective functions, and training algorithms. Requires prior experience leading pretraining for production models and strong distributed training skills. | Pretrain | 10 |
| Member of Technical Staff - Research Engineer This role focuses on optimizing and stabilizing large-scale training systems for multimodal generative models. It involves deep work on GPU performance, distributed training, low-precision techniques, and debugging complex training issues, bridging the gap between research ideas and production reality. | DataPretrain | 9 |
| 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 |
| Member of Technical Staff - VLM Research role focused on developing and integrating state-of-the-art vision-language models (VLMs) into the FLUX generative AI stack, innovating on architectures and improving multimodal understanding for enhanced generation quality and controllability. | PretrainPost-train | 9 |
| Member of Technical Staff - Post Training This role focuses on the post-training pipeline for multimodal generative models, including data strategy, reward modeling, preference optimization, distillation, and safety tuning. The goal is to improve model quality and align them with human intent, with a strong emphasis on shipping these improvements to users. | Post-train | 9 |
| Member of Technical Staff - Image / Video Generation Research role focused on training and fine-tuning large-scale diffusion models for image and video generation, involving rigorous experimentation, ablation studies, and understanding speed-quality tradeoffs in production settings. | Post-train | 9 |
| Member of Technical Staff - Model Serving / API Backend Engineer This role focuses on bridging the gap between AI research breakthroughs and production systems by building and optimizing inference services and high-performance APIs for generative models. The engineer will own the productionization of research checkpoints, ensuring low latency, high throughput, and scalability for millions of requests, while also improving monitoring and observability. | Serve | 8 |
| Member of Technical Staff - Infrastructure Engineer Infrastructure Engineer role focused on building and maintaining the large-scale training platforms and research infrastructure that powers generative AI model development, including scaling compute clusters, ensuring reliability, and optimizing performance. | Data | 7 |