At Black Forest Labs, we’re on a mission to advance the state of the art in generative deep learning for media, building powerful, creative, and open models that push what’s possible.
Born from foundational research, we continuously create advanced infrastructure to transform ideas into images and videos.
Our team pioneered Latent Diffusion, Stable Diffusion, and FLUX.1 – milestones in the evolution of generative AI. Today, these foundations power millions of creations worldwide, from individual artists to enterprise applications.
The Role
We are looking for generalist software engineers with a strong background from model hosting and serving to frontend engineering. Prior experience with diffusion models is a plus. You should enjoy working with customers, better understand their needs and assist them with BFL models, for instance with help for finetuning FLUX models for their specific use case.
As a Forward Deployed Engineering Generalist for BFL you will:
- Design and implement deep product integrations for customers, and help them with model hosting, finetuning, deployment and inference optimization
- Together with BFL’s customers, design and implement intuitive and interactive user interfaces on top of existing or new integrations of FLUX models
- Help customers to set up FLUX models in their services and ensure an strong performance in terms of latency and output quality, both for on premise deployments and BFL-hosted integrations.
- Meet with customers to identify gaps and pain points, assess their needs for BFL’s solutions, and help them to decide between BFL-hosted and on premise deployments
- Collaborate with customers to identify relevant use cases and find innovative solutions for solving these
- Identify expansion potentials for BFL’s technologies into new industry sectors across the globe
Ideal experience
- Experience in working directly with customers, iterating on solutions and providing tailored support for serving generative AI models
- Proven track record in software/forward deployed engineering
- Ability to work on a broad class of engineering problems, from model hosting and backend engineering to building intuitive frontends and UI
- Proficiency in Python and understanding of API integrations to implement basic functionality and help customers with prototyping/demo building.
- Experience in explaining and summarizing sophisticated technical concepts to both technical and non-technical audiences
- Excellent communication skills and experience in collaborating with non-technical stakeholders internally and externally, and the ability to adapt messaging to different audiences and explain complex technical concepts in simple terms with technical and non-technical audiences
Nice to have
- Prior knowledge about diffusion models and/or flow matching, and relevant finetuning and distillation techniques
- Experience in using common open source tooling around from the FLUX ecosystem such as ComfyUI and common trainer frameworks
- Experience with inference optimizations for transformer based machine learning models
- Proven ability to architect solutions in complex enterprise environments
- Contributed to open-source projects in particular in the space of diffusion models
- Experience with cloud platforms and state of the art deployment solutions for diffusion models
Base Annual Salary: $180,000 - $300,000 USD
