Currently tracking 8 active AI roles, up 17% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $180k–$300k (avg $240k).
Black Forest Labs currently has 9 active AI-related job listings. The company is hiring across multiple stages of AI development, with serving infrastructure roles making up 33% of the openings, followed by post-training, pre-training, and data roles, each at 22%. Engineering is the most frequent function, with 6 positions, while research accounts for 3. The majority of these roles are located in the United States. Frequent technical tags include fine_tuning, model_serving, vision, and multimodal.
Black Forest Labs currently has 9 active AI-related roles in our index. The most common open titles are: Developer Experience Engineer, Forward Deployed Machine Learning Engineer, Member of Technical Staff - Image / Video Generation, Member of Technical Staff - Infrastructure Engineer, Member of Technical Staff - Large Scale Data Infrastructure. Most positions are in Engineering and Research.
Black Forest Labs's active AI hiring is concentrated in: serving infrastructure (22%), post-training (22%), pre-training (22%). 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 reference: model serving, fine tuning, vision, multimodal, frontier research.
In the past 30 days, Black Forest Labs has posted 1 new AI-related role.
| Title | Stage | AI score |
|---|---|---|
| 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 |